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PhD Admissions

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The Computer Science Department PhD program is a top-ranked research-oriented program, typically completed in 5-6 years. There are very few course requirements and the emphasis is on preparation for a career in Computer Science research. 

Eligibility

To be eligible for admission in a Stanford graduate program, applicants must meet:

• Applicants from institutions outside of the United States must hold the equivalent of a United States Bachelor's degree from a college or University of recognized good standing. See detailed information by region on  Stanford Graduate Admissions website. 
• Area of undergraduate study . While we do not require a specific undergraduate coursework, it is important that applicants have strong quantitative and analytical skills; a Bachelor's degree in Computer Science is not required.

Any questions about the admissions eligibility should be directed to  [email protected] .

Application Checklist

An completed online application must be submitted by the CS Department application deadline and can be found  here .

Application Deadlines

The online application can be found here . You may submit one application for a PhD program per respective academic term.

CS PhD Course Guidelines

The following program guidelines (a.k.a model pogram) serve as a starting point for a discussion with the faculty about areas of interest.   This description of the Computer Science PhD course guidelines augments the school-wide  PhD course requirements .   Students should make themselves familiar with both.

Course Guidelines for Ph.D. Students in Computer Science

We expect students to obtain broad knowledge of computer science by taking graduate level courses in a variety of sub-areas in computer science, such as systems, networking, databases, algorithms, complexity, hardware, human-computer interaction, graphics, or programming languages.

Within our school, CS courses are roughly organized according to sub-area by their middle digit, so we expect students to take courses in a minimum of three distinct sub-areas, one of which should be theory (denoted by the middle digit of 2, or CS 231). Theory is specifically required as we expect all students to obtain some background in the mathematical foundations that underlie computer science. The intention is not only to give breadth to students, but to ensure cross-fertilization across different sub-disciplines in Computer Science.

Just as we expect all students obtaining a Ph.D. to have experience with the theoretical foundations of computer science, we expect all students to have some knowledge of how to build large software or hardware systems , on the order of thousands of lines of code, or the equivalent complexity in hardware. That experience may be evidenced by coursework or by a project submitted to the CHD for examination. In almost all cases a course numbered CS 26x or CS 24x will satisfy the requirement (exceptions will be noted in the course description on my.harvard). Students may also petition to use CS 161 for this requirement.   For projects in other courses, research projects, or projects done in internships the student is expected to write a note explaining the project, include a link to any relevant artifacts or outcomes, describe the student's individual contribution, and where appropriate obtain a note from their advisor, their class instructor, or their supervisors confirming their contributions.  The project must include learning about systems concepts, and not just writing many lines of code.   Students hoping to invoke the non-CS24x/26x/161 option must consult with  Prof. Mickens ,  Prof, Kung,  or  Prof. Idreos  well in advance of submitting their Program Plan to the CHD.  

Computer science is an applied science, with connections to many fields. Learning about and connecting computer science to other fields is a key part of an advanced education in computer science. These connections may introduce relevant background, or they may provide an outlet for developing new applications.

For example, mathematics courses may be appropriate for someone working in theory, linguistics courses may be appropriate for someone working in computational linguistics, economics courses may be appropriate for those working in algorithmic economics, electrical engineering courses may be appropriate for those working in circuit design, and design courses may be appropriate for someone working in user interfaces.

Requirements

The Graduate School of Arts & Sciences (GSAS) requires all Ph.D. students to complete 16 half-courses (“courses”, i.e., for 4 units of credit) to complete their degree. Of those 16 courses, a Ph.D. in Computer Science requires 10 letter-graded courses. (The remaining 6 courses are often 300-level research courses or other undergraduate or graduate coursework beyond the 10 required courses.)

The requirements for the 10 letter-graded courses are as follows:

• Of the 7 technical courses, at least 3 must be 200-level Computer Science courses, with 3 different middle digits (from the set 2,3,4,5,6,7,8), and with one of these three courses either having a middle digit of 2 or being CS 231 (i.e., a “theory” course).   Note that CS courses with a middle digit of 0 are valid technical courses, but do not contribute to the breadth requirement.
• At least 5 of the 8 disciplinary courses must be SEAS or SEAS-equivalent 200-level courses. A “SEAS equivalent” course is a course taught by a SEAS faculty member in another FAS department. 
• For any MIT course taken, the student must provide justification why the MIT course is necessary (i.e. SEAS does not offer the topic, the SEAS course has not been offered in recent years, etc.). MIT courses do not count as part of the 5 200-level SEAS/SEAS-equivalent courses. 
• 2 of the 10 courses must constitute an external minor (referred to as "breadth" courses in the SEAS “ Policies of the Committee on Higher Degrees [CHD] ”) in an area outside of computer science. These courses should be clearly related; generally, this will mean the two courses are in the same discipline, although this is not mandatory. These courses must be distinct from the 8 disciplinary courses referenced above.
• Students must demonstrate practical competence by building a large software or hardware system during the course of their graduate studies. This requirement will generally be met through a class project, but it can also be met through work done in the course of a summer internship, or in the course of research.
• In particular, for Computer Science graduate degrees, Applied Computation courses may be counted as 100-level courses, not 200-level courses.
• Up to 2 of the 10 courses can be 299r courses, but only 1 of the up to 2 allowed 299r courses can count toward the 8 disciplinary courses. 299r courses do not count toward the 5 200-level SEAS/SEAS-equivalent courses. If two 299r’s are taken, they can be with the same faculty but the topics must be sufficiently different.
• A maximum of 3 graduate-level transfer classes are allowed to count towards the 10 course requirement.
• All CS Ph.D. program plans must adhere to the SEAS-wide Ph.D. requirements, which are stated in the SEAS Policies of the Committee on Higher Degrees (CHD) . These SEAS-wide requirements are included in the items listed above, though students are encouraged to read the CHD document if there are questions, as the CHD document provides further explanation/detail on several of the items above.
• All program plans must be approved by the CHD. Exceptions to any of these requirements require a detailed written explanation of the reasoning for the exception from the student and the student’s research advisor. Exceptions can only be approved by the CHD, and generally exceptions will only be given for unusual circumstances specific to the student’s research program.

Requirement Notes

• Courses below the 100-level are not suitable for graduate credit.
• For students who were required to take it, CS 2091/2092 (formerly CS 290a/b or 290hfa/hfb may be included as one of the 10 courses but it does not count toward the 200-level CS or SEAS/SEAS-equivalent course requirements nor toward the SM en route to the PhD.

Your program plan  must always comply  with both our school's General Requirements, in addition to complying with the specific requirements for Computer Science. All program plans must be approved by the Committee on Higher Degrees [CHD]. Exceptions to the requirements can only be approved by the CHD, and generally will only be given for unusual circumstances specific to the student’s research program

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Pursuing A Part-Time Phd In Computer Science: What You Need To Know

Earning a PhD is the pinnacle of academic achievement in computer science, opening doors to research, teaching, and leadership roles. But taking 4+ years off work for a full-time program isn’t feasible for everyone.

Part-time PhD options allow professionals to attain this goal while continuing their careers.

If you’re short on time, here’s the key takeaway: Part-time CS PhD programs typically take 5-7 years to complete . They provide flexibility for working students but require diligence to balance school, research, and professional demands.

The Benefits of a Part-Time CS PhD

Progress academically without leaving your job.

A part-time PhD in Computer Science offers the unique opportunity to advance your academic career while still maintaining your professional commitments. This flexibility allows you to continue working in your current job, providing financial stability and practical application of your studies.

Balancing work and study can be challenging, but the rewards are worth it. By pursuing a part-time PhD, you can deepen your knowledge in your chosen field and make significant contributions to the advancement of computer science.

Network with faculty and peers in your field

One of the key advantages of pursuing a part-time PhD in Computer Science is the opportunity to network with esteemed faculty members and like-minded peers who share your passion for the subject. Interacting with experts in the field can provide valuable insights, guidance, and collaboration opportunities.

Attending conferences, workshops, and seminars can further expand your network and expose you to the latest developments in computer science. Building these connections can open doors to new opportunities and enhance your career prospects.

Strengthen research skills and resume

A part-time PhD program allows you to develop and refine your research skills, which are highly valued in the field of computer science. Through conducting in-depth research, analyzing data, and writing scholarly papers, you can enhance your ability to critically think, problem solve, and contribute to the body of knowledge in your area of expertise.

Moreover, having a PhD in Computer Science on your resume demonstrates your dedication, perseverance, and expertise, making you a highly sought-after candidate for both academic and industry positions.

Program Structure and Requirements

Reduced course load each semester.

Pursuing a part-time PhD in Computer Science offers flexibility in terms of course load. Unlike full-time students, part-time students typically take a reduced number of courses each semester. This allows them to balance their academic commitments with other personal and professional responsibilities.

By taking fewer courses at a time, part-time students can focus on their coursework more effectively and ensure a better understanding of the material.

Original dissertation research

The cornerstone of a part-time PhD program in Computer Science is the dissertation research. Students are required to embark on an original research project under the guidance of a faculty advisor. This research should contribute to the existing body of knowledge in the field and demonstrate a deep understanding of a specific area of computer science.

The research can involve developing new algorithms, designing innovative software systems, or exploring cutting-edge technologies.

Qualifying exams and proposal defense

Part-time PhD students in Computer Science are typically required to pass qualifying exams to demonstrate their readiness for conducting research. These exams assess the student’s knowledge and understanding of the core concepts in the field.

Once the exams are passed, students need to prepare a research proposal outlining the objectives, methodology, and expected contributions of their dissertation. The proposal is then defended in front of a committee of faculty members who evaluate its feasibility and significance.

It’s important to note that the specific structure and requirements of a part-time PhD program in Computer Science may vary depending on the institution. It is advisable to consult the program’s official website or contact the program coordinator for more detailed information.

Finding the Right Program

When pursuing a part-time PhD in Computer Science, finding the right program is crucial for success. Here are some key factors to consider:

On-campus and online options

One of the first decisions to make is whether to pursue your PhD on-campus or online. On-campus programs offer the benefit of face-to-face interactions with professors and fellow students, while online programs provide flexibility for those who are working or have other commitments.

It’s important to weigh the pros and cons of each option and choose the one that aligns best with your lifestyle and goals.

Focus on faculty research expertise

Another important factor to consider when choosing a program is the faculty’s research expertise. Look for programs where the faculty members have research interests and expertise that align with your own.

This will ensure that you receive guidance and mentorship from experts in your field of interest. Additionally, professors with strong research backgrounds can provide valuable networking opportunities and connections in the industry.

Funding availability

Funding is a significant consideration for many part-time PhD students. Look for programs that offer funding options such as scholarships, grants, or assistantships. These can help alleviate the financial burden and allow you to focus on your studies.

It’s also worth exploring external funding opportunities from organizations or government agencies that support research in your field.

Managing Your Time Effectively

Stay organized with schedules and goals.

When pursuing a part-time PhD in computer science, time management becomes crucial. It is important to create a schedule that includes dedicated study hours, research time, and coursework completion. By setting goals for each week or month, you can track your progress and ensure that you are staying on track.

One effective strategy is to use a planner or a digital calendar to keep track of deadlines, meetings, and other important events. By having a visual representation of your commitments, you can prioritize your tasks and allocate time accordingly.

Additionally, breaking down larger tasks into smaller, manageable chunks can help you stay organized and prevent overwhelm. By setting realistic goals for each study session, you can make progress towards your PhD while still managing other responsibilities.

Communicate needs clearly at work

When pursuing a part-time PhD, it is essential to communicate your needs with your employer or colleagues. Letting them know about your academic commitments and the time required for your studies can help them understand your availability and make necessary adjustments.

Consider having a conversation with your supervisor or manager to discuss your situation and explore potential flexible working arrangements. This could include adjusting your work schedule, reducing your workload, or even exploring opportunities for research collaboration between your job and your PhD.

Open and honest communication can go a long way in ensuring that both your work and academic responsibilities are managed effectively.

Leverage support systems

Pursuing a part-time PhD can be challenging, but you don’t have to do it alone. It is crucial to leverage the support systems available to you.

Reach out to your academic advisor or supervisor for guidance and support. They can provide valuable insights on managing your time, selecting courses, and balancing your academic and work commitments.

Additionally, consider joining or forming study groups with fellow part-time PhD students. Collaborating with others who are facing similar challenges can provide a sense of camaraderie and support. You can share study materials, discuss research ideas, and offer each other encouragement along the way.

Lastly, don’t forget about the support of your family and friends. Let them know about your academic journey and the challenges you may face. Their understanding and encouragement can help you stay motivated and focused on your goals.

Remember, pursuing a part-time PhD in computer science requires dedication, discipline, and effective time management. By staying organized, communicating your needs, and leveraging support systems, you can successfully navigate this exciting academic journey while maintaining a balance with your work and personal life.

Completion, Careers and Next Steps

Job prospects post-phd.

Completing a part-time PhD in computer science opens up a world of exciting job prospects. With a doctoral degree in this field, you are well-equipped to pursue highly specialized positions in both industry and academia.

The demand for computer science professionals continues to grow, and obtaining a PhD can give you a competitive edge in the job market. According to the Bureau of Labor Statistics, the employment of computer and information research scientists is projected to grow 15 percent from 2019 to 2029, much faster than the average for all occupations.

This means that there will be ample opportunities for individuals with advanced degrees in computer science.

Potential teaching and research roles

One of the key benefits of earning a PhD in computer science is the opportunity to pursue teaching and research roles. Many universities and research institutions are constantly seeking experts in the field to join their faculty and contribute to cutting-edge research.

As a PhD holder, you can become a professor, teaching and mentoring the next generation of computer scientists. Additionally, you can engage in research projects, pushing the boundaries of knowledge in the field and making significant contributions to the advancement of technology.

The opportunity to share your expertise and make a lasting impact in the academic community is truly rewarding.

Higher salaries and senior positions

Earning a PhD in computer science can also lead to higher salaries and senior positions. With the advanced knowledge and skills gained during your doctoral studies, you become a valuable asset to companies and organizations.

Employers often recognize the expertise and dedication required to complete a PhD, and are willing to offer higher salaries to attract and retain top talent. In addition, holding a doctoral degree can open doors to senior management and leadership positions, where you can have a greater influence on strategic decisions and shape the direction of the company.

According to a survey conducted by the National Association of Colleges and Employers, computer science PhD graduates earned an average starting salary of $123,000 in 2020, significantly higher than those with a bachelor’s or master’s degree.

While requiring diligence and time management skills, part-time computer science PhD programs make this high-level credential attainable for busy professionals. From strengthening your research abilities to opening new career doors, the long-term benefits of earning a PhD on a flexible schedule are immense.

If you’re willing to balance work, research, and coursework, a part-time CS PhD can help you achieve your pinnacle academic and career aspirations.

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Ph.D. in Computer Science overview

Looking to make your mark on the computer science community? Our doctoral program prepares students for careers focused on research and innovation. Whether you dream of working in the industry or in academia, a Ph.D. in computer science is the jumping off point for ground breaking discovery.

• General degree information
• Credit Requirements
• Thesis credits
• Things to remember
• Degree Progress

The Ph.D. in Computer Science is a research degree which culminates in a unique dissertation that demonstrates original and creative research. The program consists of three components: coursework, research, and thesis preparation.

Early on in your career as a graduate student, you will take courses to fulfill background, breadth and supporting program requirements. You will also take courses that help to develop and refine your research writing skills; these skills include information analysis and synthesis as well as written and verbal presentation capabilities. This part of your graduate career ends when you cross the threshold presented by the  Preliminary Oral and Written Examinations  (WPE and OPE). Taken in conjunction, these examinations serve as an early test of your research ability.

Once you have passed the WPE and OPE, you will be formally admitted to Ph.D. candidacy and are ready to begin the second phase of your career as a doctoral student. During this phase, your coursework lightens and your research increases as you focus on the definition and pursuit of your specific thesis topic and begin to prepare for your  Thesis Proposal Examination . The Thesis Proposal Examination should be taken 1-2 years after passing the Preliminary Oral Examination and is a presentation pertaining to research directly related to your thesis proposal. This examination will test the full range of your expertise regarding your thesis topic in order to evaluate your preparation for thesis research and the suitability of your thesis research plan.

Once you pass the Thesis Proposal Examination, you will be in the full swing of research. During this stage, you will synthesize all of the skills you have learned up to this point and use them to distill the material that will become the core of your doctoral thesis. Your days and nights will be filled with intense thesis preparation and research into your thesis topic and finally you will produce a complete thesis dissertation document which you will defend orally during your  Final Oral Examination and Thesis Defense .  The successful completion of these activities yields your Doctor of Philosophy (Ph.D.) in Computer Science!

Throughout your career as a doctoral student you will receive support from your Academic Advisor(s), peer and research groups, and the departmental program administrator as well as a number of individuals across campus who work to best facilitate your progress through your degree program. Our primary goal is to make sure that your experience is positive, productive, and prepares you for a successful career beyond the University of Minnesota. The entirety of the Ph.D. process is complex and at times, rife with academic and administrative requirements. If you have questions regarding your individual degree plan, please do not hesitate to reach out to your advisor, the Director of Graduate Studies or the Graduate Program Coordinator for help.

A total of 55 credits are required to complete the Ph.D. in Computer Science. This includes 31 coursework credits and 24 thesis credits with a GPA of 3.45 or higher.

Coursework credits

Each student must complete 31 credits of graduate coursework, including:

• 16 graduate credits from 5xxx or 8xxx courses with a CSCI designator (with a grade of C- or better)
• 15 credits of  breadth courses  (5 courses), at least one from each category.
• 1 credit of CSCI colloquium (CSCI 8970)
• 6 credits of supporting program coursework or 12 credits from a minor program
• CSCI 8001/8002 unless advised otherwise by research advisor (Introduction to Research in Computer Science I and II)
• Other graduate-level credits to reach a total of at least 31 credits which may include related field courses from programs other than CSCI or courses for a graduate minor

Students have eight calendar years to complete their degree per University requirements.

Transfer credits from a previously acquired M.S. degree may apply to your Ph.D. program. Please speak with the Graduate Program Coordinator for information on transfer credit.

Breadth  coursework consists of five (5) courses (typically 15 credits) taken within three (3) subject areas. The breadth requirement exists to help expose the student to diverse computer science research topics and methods. There is 3.45 GPA minimum requirement for this coursework.

Supporting program courses

Supporting program courses are defined as a minimum of six (6) credits from a supporting program outside of the computer science department. These six credits can be a part of the 12 credits counted towards a minor. A minor is optional for the Ph.D. in Computer Science.

Background knowledge

Background knowledge  courses cover concepts that are integral to a minimal core body of knowledge that all computer science Ph.D. students are expected to posses. These concepts are required prerequisites and all students in the Ph.D. program are required to fulfill these background requirements.

In addition to coursework credits, a minimum of 24 thesis credits are required in order to complete the Ph.D. program. These courses may only be taken following the completion of the WPE/OPE and admission of a student to Ph.D. candidacy.

It is the recommendation of the department that you maximize the thesis credits you take each semester and it is our hope that you will complete the thesis credits in two (2) semesters. Most students will be able to take half in one semester and the other half the next semester. If you still have some classes to take, you can register for the class(es) and then register thesis credits for the rest of the credits, up to the maximum allowed each semester of 14 credits total

When you have completed all of your thesis credits, you will be put in a reduced fringe classification, which allows you to only register for one credit, CSCI 8444 which is designated as the Ph.D. full-time equivalent credit. This credit gives you full-time status for your visa requirements for international students and also full-time status if you hold a graduate assistantship. Your assistantship will only pay for one credit, so if you take any additional credits after you have completed all of your thesis credits, the tuition for those credits will be your responsibility.

For international students who wish to do CPT during the summer and to register for CPT in the fall, you should not register for CSCI 8444 but instead request a reduced course  load  and submit to ISSS. For those who hold an assistantship, you must also submit a  Special Graduate Assistant Registration Tuition Benefits Status Request  form. This form must be submitted before the semester begins and is to be signed by your advisor, your employer (your advisor if an RA, by the DGS if TA) and then by the DGS. It should be submitted to the office and we will make sure it has the DGS signature and then fax it to the Grad Assistant Office. If you have any questions about the distribution of course and thesis credits over your career, please be sure to discuss with the Graduate Program Coordinator.

• Students who take six (6) credits or more are considered full-time graduate students.  All international students and students who hold a graduate assistantship, fellowship, or traineeship are required to be full-time students .
• Almost all of the graduate level courses in computer science (5000 level and above) are 3 credits each.
• Special topics courses (CSCI 5980 or 8980) are courses taught one time only and are good options if the topic is of interest to you. However, please note that these do not count towards breadth requirements.
• All computer science courses must be taken A/F (unless only offered S/N, such as colloquium or plan B project), and no more than one-third of the courses that will count towards your degree can be taken on the S/N basis.
• Students must maintain a minimum GPA of 3.45 for courses counting towards your degree and no courses with a grade below a C- can be included.
• Students in the Doctoral program can use a maximum six (6) credits of directed research or independent study for elective credits. This is defined as CSCI 5991/5994/8991/8994

All requirements for the doctoral degree must be completed and the degree awarded within  five calendar years after passing the preliminary oral examination . Graduate School policy dictates a departmental  annual review  of Ph.D. progress for all students. Each fall, computer science Ph.D. students will be required to complete an annual review form. This form is used by the student’s research advisor to note student progress through the program. All forms are reviewed by the Director of Graduate Studies for satisfactory progress. Progress Guidelines are available in Appendix A of the Graduate Student Handbook.

The Graduate Program Coordinator can answer most questions and advise students on degree requirements, department procedures, or general issues about being a graduate student. All new students are expected to meet with her upon arrival as well as several times throughout your graduate career in order to best facilitate your program.

The Director of Graduate Studies is the official advisor of record for all students, unless an advisor was assigned at the time of admission. Only  faculty with graduate education responsibilities  are eligible to serve as advisors for graduate students. The advisor-advisee relationship is a mutual and an advisor must agree to advise any student. Once a student determines his or her advisor they will fill out a  Declaration of Advisor  form. A student may change advisors at any time using the same form. Please note that the new and the previous advisor must sign to acknowledge this change.

Most Ph.D. students have been assigned advisors in their field of interest at the time of entry into the university. Students are encouraged to talk to their assigned advisor as well as other faculty members in their interest area to determine if their assigned advisor is best suited to their research goals. It is not uncommon to discover that your permanent research advisor is different from your pre-assigned one. You are expected to take some time to look around, talk with professors and other graduate students, and then talk with your prospective advisor.  We expect you to find an advisor by the end of your first year in the program.  Advising is a mutually voluntary arrangement. You never will be obligated to work with someone against your choice, and no faculty member is obligated to take on any particular student.

For questions regarding the advising process please contact the  Director of Graduate Studies .

Stephen Guy

Associate Professor, Director of Graduate Studies

5-225F Keller Hall 612-625-3368 [email protected]

Joseph Nieszner

Senior Graduate Program Coordinator

330G Lind Hall [email protected]   [email protected]

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Computer Science Ph.D. Program

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The Cornell Ph.D. program in computer science is consistently ranked among the top six departments in the country, with world-class research covering all of computer science. Our computer science program is distinguished by the excellence of the faculty, by a long tradition of pioneering research, and by the breadth of its Ph.D. program. Faculty and Ph.D. students are located both in Ithaca and in New York City at the Cornell Tech campus . The Field of Computer Science also includes faculty members from other departments (Electrical Engineering, Information Science, Applied Math, Mathematics, Operations Research and Industrial Engineering, Mechanical and Aerospace Engineering, Computational Biology, and Architecture) who can supervise a student's Ph.D. thesis research in computer science.

Over the past years we've increased our strength in areas such as artificial intelligence, computer graphics, systems, security, machine learning, and digital libraries, while maintaining our depth in traditional areas such as theory, programming languages and scientific computing.  You can find out more about our research here . 

The department provides an exceptionally open and friendly atmosphere that encourages the sharing of ideas across all areas. 

Cornell is located in the heart of the Finger Lakes region. This beautiful area provides many opportunities for recreational activities such as sailing, windsurfing, canoeing, kayaking, both downhill and cross-country skiing, ice skating, rock climbing, hiking, camping, and brewery/cider/wine-tasting. In fact, Cornell offers courses in all of these activities.

The Cornell Tech campus in New York City is located on Roosevelt Island.  Cornell Tech  is a graduate school conceived and implemented expressly to integrate the study of technology with business, law, and design. There are now over a half-dozen masters programs on offer as well as doctoral studies.

FAQ with more information about the two campuses .

Ph.D. Program Structure

Each year, about 30-40 new Ph.D. students join the department. During the first two semesters, students become familiar with the faculty members and their areas of research by taking graduate courses, attending research seminars, and participating in research projects. By the end of the first year, each student selects a specific area and forms a committee based on the student's research interests. This “Special Committee” of three or more faculty members will guide the student through to a Ph.D. dissertation. Ph.D. students that decide to work with a faculty member based at Cornell Tech typically move to New York City after a year in Ithaca.

The Field believes that certain areas are so fundamental to Computer Science that all students should be competent in them. Ph.D. candidates are expected to demonstrate competency in four areas of computer science at the high undergraduate level: theory, programming languages, systems, and artificial intelligence.

Each student then focuses on a specific topic of research and begins a preliminary investigation of that topic. The initial results are presented during a comprehensive oral evaluation, which is administered by the members of the student's Special Committee. The objective of this examination, usually taken in the third year, is to evaluate a student's ability to undertake original research at the Ph.D. level.

The final oral examination, a public defense of the dissertation, is taken before the Special Committee.

To encourage students to explore areas other than Computer Science, the department requires that students complete an outside minor. Cornell offers almost 90 fields from which a minor can be chosen. Some students elect to minor in related fields such as Applied Mathematics, Information Science, Electrical Engineering, or Operations Research. Others use this opportunity to pursue interests as diverse as Music, Theater, Psychology, Women's Studies, Philosophy, and Finance.

The computer science Ph.D. program complies with the requirements of the Cornell Graduate School , which include requirements on residency, minimum grades, examinations, and dissertation.

The Department also administers a very small 2-year Master of Science program (with thesis). Students in this program serve as teaching assistants and receive full tuition plus a stipend for their services.

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Computer Science, Ph.D.

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We have a thriving Ph.D. program with approximately 80 full-time Ph.D. students hailing from all corners of the world. Most full-time Ph.D. students have scholarships that cover tuition and provide a monthly stipend. Admission is highly competitive. We seek creative, articulate students with undergraduate and master's degrees from top universities worldwide. Our  current research strengths  include data management and analysis, cybersecurity, computer games, visualization, web search, graphics, vision and image processing, and theoretical computer science.

This degree program offers interested students opportunities to do their research abroad, under the supervision of faculty at NYU Shanghai or  NYU Abu Dhabi .

• View the Computer Science Ph.D. program flyer
• Admissions requirements for the Ph.D. Program.
• Find out more about general  Admission Requirements .

To receive a Ph.D. in Computer Science at the NYU Tandon School of Engineering, a student must:

• satisfy a breadth course requirement, intended to ensure broad knowledge of computer science,
• satisfy a depth requirement, consisting of an oral qualifying exam presentation with a written report, to ensure the student's ability to do research,
• submit a written thesis proposal and make an oral presentation about the proposal,
• write a Ph.D. thesis that must be approved by a dissertation guidance committee and present an oral thesis defense, and
• satisfy all School of Engineering requirements for the Ph.D. degree, as described in the NYU Tandon School of Engineering bulletin, including graduate study duration, credit points, GPA, and time-to-degree requirements.

Upon entering the program, each student will be assigned an advisor who will guide them in formulating an individual study plan directing their course choice for the first two years. The department will hold an annual Ph.D. Student Assessment Meeting, in which all Ph.D. students will be formally reviewed.

Note: for pre-fall 2015 Ph.D. students, please see the pre-fall 2015 Ph.D. Curriculum.

Program Requirements

Details about Breadth and Depth Requirements, Thesis Proposal and Presentation, and Thesis Defense can be found in the NYU Bulletin.

Program Details

Each incoming Ph.D. student will be assigned to a research advisor, or to an interim advisor, who will provide academic advising until the student has a research advisor. The advisor will meet with the student when the student enters the program to guide the student in formulating an Individual Study Plan. The purpose of the plan is to guide the student’s course choice for the first two years in the program and to ensure that the student meets the breadth requirements. The plan may also specify additional courses to be taken by the student in order to acquire necessary background and expertise. Subsequent changes to the plan must be approved by the advisor.

Sample Plan of Study

In order to obtain a Ph.D. degree, a student must complete a minimum of 75 credits of graduate work beyond the BS degree, including at least 21 credits of dissertation. A Master of Science in Computer Science may be transferred as 30 credits without taking individual courses into consideration. Other graduate coursework in Computer Science may be transferred on a course-by-course basis. Graduate coursework in areas other than Computer Science can be transferred on a course-by-course basis with approval of the Ph.D. Committee (PHDC). The School of Engineering places some limits on the number and types of transfer credits that are available. Applications for transfer credits must be submitted for consideration before the end of the first semester of matriculation. 

All Ph.D. students will be formally reviewed each year in a Ph.D. Student Assessment Meeting. The review is conducted by the entire CSE faculty and includes at least the following items (in no particular order):

• All courses taken, grades received, and GPAs.
• Research productivity: publications, talks, software, systems, etc.
• Faculty input, especially from advisors and committee members.
• Student’s own input.
• Cumulative history of the student's progress.

As a result of the review, each student will be placed in one of the following two categories, by vote of the faculty:

• In Good Standing: The student has performed well in the previous semester and may continue in the Ph.D. program for one more year, assuming satisfactory academic progress is maintained.
• Not in Good Standing: The student has not performed sufficiently well in the previous year. The consequences of not being in good standing will vary, and may include being placed on probation, losing RA/GA/TA funding, or not being allowed to continue in the Ph.D. program.

Following the review, students will receive formal letters which will inform them of their standing. The letters may also make specific recommendations to the student as to what will be expected of them in the following year. A copy of each student’s letter will be placed in the student’s file.

Quick Links

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Program Admissions Chair

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Rachel Greenstadt

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Nektarios Tsoutsos

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Phd program, find your passion for research.

Duke Computer Science gives incoming students an opportunity to investigate a range of topics, research problems, and research groups before committing to an advisor in the first year. Funding from the department and Duke makes it possible to attend group meetings, seminars, classes and colloquia. Students may work on multiple problems simultaneously while finding the topic that will motivate them through their first project. Sharing this time of learning and investigation with others in the cohort helps create lasting collaborators and friends.

Write a research proposal the first year and finish the research the second under the supervision of the chosen advisor and committee; present the research results to the committee and peers. Many students turn their RIP work into a conference paper and travel to present it.

Course work requirements are written to support the department's research philosophy. Pass up to four of the required six courses in the first two years to give time and space for immersing oneself in the chosen area.

Years three through five continue as the students go deeper and deeper into a research area and their intellectual community broadens to include collaborators from around the world. Starting in year three, the advisor funds the student's work, usually through research grants. The Preliminary exam that year is the opportunity for the student to present their research to date, to share work done by others on the topic, and to get feedback and direction for the Ph.D. from the committee, other faculty, and peers.

Most Ph.D students defend in years five and six. While Duke and the department guarantee funding through the fifth year, advisors and the department work with students to continue support for work that takes longer.

Teaching is a vital part of the Ph.D. experience. Students are required to TA for two semesters, although faculty are ready to work with students who want more involvement. The Graduate School's Certificate in College Teaching offers coursework, peer review, and evaluation of a teaching portfolio for those who want to teach. In addition, the Department awards a Certificates of Distinction in Teaching for graduating PhD students who have demonstrated excellence in and commitment to teaching and mentoring.

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Computer Science (4 Year Programme) MPhil/PhD

London, Bloomsbury

The PhD programme in UCL Computer Science is a 4-year programme, in which you will work within research groups on important and challenging problems in the development of computer science. We have research groups that cover many of the leading-edge topics in computer science , and you will be supervised by academics at the very forefront of their field.

UK tuition fees (2024/25)

Overseas tuition fees (2024/25), programme starts, applications accepted.

• Entry requirements

A UK Master's degree in a relevant discipline with Merit, or a minimum of an upper second-class UK Bachelor's degree in a relevant discipline, or an overseas qualification of an equivalent standard. Work experience may also be taken into account.

The English language level for this programme is: Level 1

UCL Pre-Master's and Pre-sessional English courses are for international students who are aiming to study for a postgraduate degree at UCL. The courses will develop your academic English and academic skills required to succeed at postgraduate level.

Further information can be found on our English language requirements page.

If you are intending to apply for a time-limited visa to complete your UCL studies (e.g., Student visa, Skilled worker visa, PBS dependant visa etc.) you may be required to obtain ATAS clearance . This will be confirmed to you if you obtain an offer of a place. Please note that ATAS processing times can take up to six months, so we recommend you consider these timelines when submitting your application to UCL.

Equivalent qualifications

Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website .

International applicants can find out the equivalent qualification for their country by selecting from the list below. Please note that the equivalency will correspond to the broad UK degree classification stated on this page (e.g. upper second-class). Where a specific overall percentage is required in the UK qualification, the international equivalency will be higher than that stated below. Please contact Graduate Admissions should you require further advice.

About this degree

On this PhD programme, you will work within research groups on challenging computer science projects.

Our research groups cover leading-edge topics , and our academics are at the forefront of their field.

The research groups, the department , and the college, provide numerous opportunities to learn more about your field and the skills required to develop your research and future careers.

Who this course is for

This programme is best suited for people wishing to embark on an academic career, as well as those interested in finding work in industry. You will be assigned a first and second supervisor, who will guide you in the development of your research project and your abilities as a researcher. The research groups, the department, and the college, provide numerous opportunities for you to learn more about your field (e.g. seminars, conferences, and journal clubs) and the skills required for you to develop your research and future careers (e.g. training courses). Many of our students have had their research results published and recognised at leading international conferences during their time on the PhD programme.

What this course will give you

UCL is ranked 9th globally in the latest QS World University Rankings (2024), giving you an exciting opportunity to study at one of the world's best universities.

UCL Computer Science is recognised as a world leader in teaching and research. The department was ranked first in England and second in the UK for research power in Computer Science and Informatics in the most recent Research Excellence Framework ( REF2021 ). You will learn from leading experts with an outstanding reputation in the field. 

Code written at UCL is used across all 3G mobile networks for instant messaging and videoconferencing; medical image computing has led to faster prostate cancer diagnosis and has developed tools to help neurosurgeons avoid damaging essential communication pathways during brain surgery; and our human-centred approach to computer security has transformed the UK government's delivery of online security.

This MPhil/PhD in Computer Science is a research degree programme that will not only challenge and stimulate you, but also has the potential to lead to a varied and interesting career and introduce you to valuable contacts in academia and the industry.

The foundation of your career

Your employability will be greatly enhanced by working alongside world-leading researchers in cutting-edge research areas such as virtual environments, networked systems, human-computer interaction and financial computing. UCL's approach is multi-disciplinary and UCL Computer Science shares ideas and resources from across all departments of Faculty of Engineering Sciences and beyond. Our alumni have a successful record of finding work, or have founded their own successful start-up companies, because they have an excellent understanding of the current questions which face industry and have the skills and the experience to market innovative solutions.

Employability

UCL Computer Science graduates secure careers in a variety of organisations, including global IT consultancies, City banks and specialist companies in manufacturing industries.

The department takes pride in helping students in their career choices and offers placements and internships with numerous start-up technology companies, including those on Silicon Roundabout, world-leading companies such as Google, Skype and Facebook, and multi national finance companies, including Morgan Stanley, Deutsche Bank and JP Morgan.

Our graduates secure roles such as applications developers, information systems managers, IT consultants, multimedia programmers, software engineers and systems analysts in companies such as Microsoft, Cisco, Bloomberg, PwC and IBM.

UCL Computer Science is located in the heart of London and subsequently has strong links with industry. You will have regular opportunities to undertake internships at world-leading research organisations. We frequently welcome industry executives to observe your project presentations, and we host networking events with technology entrepreneurs.

You will also benefit from a location close to the City of London and Canary Wharf to work on projects with leading global financial companies. London is also home to numerous technology communities, for example the Graduate Developer Community, who meet regularly and provide mentors for students interested in finding developer roles when they graduate.

Teaching and learning

You are assigned a first and second supervisor who you will meet regularly. You are also assigned a research group who normally meet regularly for research seminars and related activities in the department.

You will participate in three vivas during the course of your study. These are useful feedback opportunities and allow you to demonstrate your understanding of the literature, your progress in your research and eventually, your final thesis and research. For each viva, you will be expected to produce a detailed report of your work to date and to attend a 'verbal exam' with supervisors and/or external academics/experts.

During your research degree, you will have regular meetings with your primary supervisor, in addition to contact with your secondary supervisor and participation in group meetings. Full-time study should comprise of 40 hours per week .

Research areas and structure

• Bioinformatics: protein structure; genome analysis; transmembrane protein modelling; de novo protein design methods; exploiting grid technology; mathematical modelling of biological processes
• Financial computing: software engineering; computational statistics and machine learning; mathematical modelling
• Human centred systems: usability of security and multimedia systems; making sense of information; human error and cognitive resilience
• Information security: human and organisational aspects of security; privacy-enhancing technologies; cryptography and cryptocurrencies; cybersecurity in public policy and international relations; systems security and cybercrime
• Intelligent systems: knowledge representation and reasoning; machine learning
• Media futures: digital rights management; information retrieval; computational social science; recommender systems
• Networks: internet architecture; protocols; mobile networked systems; applications and evolution; high-speed networking
• Programming Principles, Verification and Logic’: logic and the semantics of programs; automated tools for verification and program analysis; produce mathematically rigorous concepts and techniques that aid in the construction and analysis of computer systems; applied logic outreach in AI, security, biology, economics
• Software systems engineering: requirements engineering; software architecture; middleware technologies; distributed systems; software tools and environments; mobile computing
• Virtual environments: presence, virtual characters; interaction; rendering; mixed reality
• Vision and imaging science: face recognition; medical image analysis; statistical modelling of colour information; inverse problems and building mathematical models for augmented reality; diffusion tensor imaging

Research environment

UCL Computer Science is one of the leading university centres for computer science research in Europe. The department is very well-connected with research groups across the university, and is involved in many exciting multi-disciplinary research projects.

Furthermore, research groups in the department are heavily involved in collaborative research and development projects with other universities and with companies in the UK and internationally. UCL provides significant support for technology transfer, and in particular for technology start-ups, and the department has an increasingly successful record of spin-out companies including a number of spin-outs that have been acquired by Google, Facebook, Amazon, etc.

Month 0 Registration - initially MPhil registration.

Month 0-6 - General reading, directed by the supervisor, in the area of interest. This should bring you up to the sharp end of the area and allow you to appreciate what the research problems are.

Months 6-9 - More detailed reading, aimed at becoming expert enough to tackle a thesis project. A small focused project is in order here to pin the reading on. A report on the year's activities should begin to be prepared.

Month 9 - FORMAL 1ST-YEAR VIVA (10-12 for Part-time) This is the first major examination, and must take place no more than 9 months from the start date. A feedback activity. Given a read of your report, the supervisor, 2nd supervisor and an 'assessor' review the work done with the aim of providing you with proper feedback on your work. This is also a good opportunity to get feedback for the Transfer Viva and is often used as a “mock transfer”.

Months 12-18 - FORMAL TRANSFER VIVA (15-21 for Part-time) Also known as the “Upgrade Viva” - this is where you would upgrade your expected qualification from MPhil to PhD. A substantial project report is expected demonstrating the ability to conduct research, with initial research results, and a plan for completion of the work and writing of the thesis. The outcome of the viva will determine whether you are allowed to transfer registration from MPhil to PhD.

Months 24-36 - Thesis project work being tidied up and turned into a unified piece of work. Thesis writing being planned and chapters being drafted. You are now eligible for Completing Research Status

Month 36 - MOCK VIVA (48-60 for Part-time) A draft thesis and mock viva. This is to be attended by the supervisor, second supervisor and assessor and any others thought relevant. Thesis submission forms (aka Entry forms) completed and submitted.

Months 36-42 - Complete the writing of the thesis.

Month 42 - (60-72 for Part-time) Submit thesis.

See full-time summary

Accessibility

Details of the accessibility of UCL buildings can be obtained from AccessAble accessable.co.uk . Further information can also be obtained from the UCL Student Support and Wellbeing team .

Fees and funding

Fees for this course.

The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Where the programme is offered on a flexible/modular basis, fees are charged pro-rata to the appropriate full-time Master's fee taken in an academic session. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website: ucl.ac.uk/students/fees .

Additional costs

As each research project is unique in nature, the AFE (Additional Fee Element) is calculated on a student-by-student basis and is determined by your academic supervisor. Please contact your supervisor for further details.

A student conference and travel fund is available to students within the department to help with costs associated with attending and presenting at conferences. Applications are considered on a case-by-case basis.

For more information on additional costs for prospective students please go to our estimated cost of essential expenditure at Accommodation and living costs .

Funding your studies

UCL offers various funding opportunities for postgraduate students. Please see UCL's Scholarships website for more information.

The department offers funding for overseas and UK students. Please see the Computer Science website for more information.

Home students will have the opportunity to apply for EPSRC DTP Studentships where available.

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website .

CSC-UCL Joint Research Scholarship

Value: Fees, maintenance and travel (Duration of programme) Criteria Based on academic merit Eligibility: EU, Overseas

Deadlines and start dates are usually dictated by funding arrangements so check with the department or academic unit to see if you need to consider these in your application preparation. All applicants are asked to identify and contact potential supervisors before making an application. For more information see our How to apply page.

Please note that you may submit applications for a maximum of two graduate programmes (or one application for the Law LLM) in any application cycle.

Choose your programme

Please read the Application Guidance before proceeding with your application.

Year of entry: 2024-2025

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PhD Computer Science / Overview

Year of entry: 2024

• View full page

The standard academic entry requirement for this PhD is an upper second-class (2:1) honours degree in a discipline directly relevant to the PhD (or international equivalent) OR any upper-second class (2:1) honours degree and a Master’s degree at merit in a discipline directly relevant to the PhD (or international equivalent).

Other combinations of qualifications and research or work experience may also be considered. Please contact the admissions team to check.

Full entry requirements

Apply online

In your application you’ll need to include:

• The name of this programme
• Your research project title (i.e. the advertised project name or proposed project name) or area of research
• Your proposed supervisor’s name
• If you already have funding or you wish to be considered for any of the available funding
• A supporting statement (see 'Advice to Applicants' for what to include)
• Details of your previous university level study
• Names and contact details of your two referees.

Find out how this programme aligns to the UN Sustainable Development Goals , including learning which relates to:

Goal 4: Quality education

Goal 8: decent work and economic growth, goal 9: industry, innovation and infrastructure, goal 17: partnerships for the goals, programme options.

Programme description

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The PhD is a three-year (or six year, if taken part-time) degree resulting in a substantial thesis.

The Department of Computer Science is one of the largest in the UK covering a huge spectrum of Computer Science topics. We currently have research groups ranging from Advanced Processor Technologies to Text Mining.

Our core Computer Science research is augmented by interdisciplinary research taking place at the interface with discipline areas including mathematics, physics, medicine and biology.

A detailed overview of the Department's research groups and core and interdisciplinary research themes is available in the 'research' area of our website and you can identify a possible project from our list of available projects .

For entry in the academic year beginning September 2024, the tuition fees are as follows:

• PhD (full-time) UK students (per annum): Band A £4,786; Band B £7,000; Band C £10,000; Band D £14,500; Band E £24,500 International, including EU, students (per annum): Band A £28,000; Band B £30,000; Band C £35,500; Band D £43,000; Band E £57,000
• PhD (part-time) UK students (per annum): Band A £2393; Band B £3,500; Band C £5,000; Band D £7,250; Band E 12,250 International, including EU, students (per annum): Band A £14,000; Band B £15,000; Band C £17,750; Band D £21,500; Band E £28,500

Further information for EU students can be found on our dedicated EU page.

The programme fee will vary depending on the cost of running the project. Fees quoted are fully inclusive and, therefore, you will not be required to pay any additional bench fees or administration costs.

All fees for entry will be subject to yearly review and incremental rises per annum are also likely over the duration of the course for Home students (fees are typically fixed for International students, for the course duration at the year of entry). For general fees information please visit the postgraduate fees page .

Always contact the Admissions team if you are unsure which fees apply to your project.

Scholarships/sponsorships

There are a range of scholarships, studentships and awards at university, faculty and department level to support both UK and overseas postgraduate researchers.

To be considered for many of our scholarships, you’ll need to be nominated by your proposed supervisor. Therefore, we’d highly recommend you discuss potential sources of funding with your supervisor first, so they can advise on your suitability and make sure you meet nomination deadlines.

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PhD Program Admissions

Applying to our PhD Program

We’re thrilled that you are interested in our PhD program in computer science! This page provides an overview of the application process, some guidelines, and answers to specific questions. Please check our FAQ before emailing [email protected] with any questions not answered here.

Our program accepts a large number of applicants each year from a diverse range of backgrounds. Our applicants come directly from undergraduate or master’s programs, as well as industry positions, and from within United States and numerous countries around the world.

Visit the interactive PhD program statistics page   to view historical program data pertaining to admissions, enrollment, retention/attrition/completion, and time to degree conferral. (Select “ Computer Science” from the “Choose Program” drop-down menu.)

Ready to start your PhD application?

We’re ready for you. Click on the link below to start your application to become a PhD student at Johns Hopkins University

The Application: General Advice

The most important question we ask when reviewing applications is "Will this individual excel at research?" Every part of your application is helpful insofar as it answers this question. The three major components of an application are the statement, letters of recommendation, and grades.

This is one of the most important parts of your application; it lets us get to know you and creates a narrative of your academic career and future plans. Before you write your statement, start by thinking about what you want us to learn about you. Make a list of important achievements, perspectives, and goals. Build your statement around this list. We are looking for students who have made the most of the opportunities they have been presented with and who are smart, creative, and motivated. Keep in mind that we also have your CV and letters of recommendation, so we don’t necessarily need a list of all your accomplishments. However, your statement can fill in the narrative around what you did and, more specifically, why you did it. What motivates you? What are your research interests and why? These details aren’t found elsewhere in your application, so focus on them in your statement.

There are a few things we suggest not including in your statement. While it’s tempting to give a rationale for why you are applying to our program, don’t include it if it’s uninformed. Consider: “I want to apply to Johns Hopkins because it’s one of the premiere academic programs.” We know that already! If you do have specific reasons to be interested in our program (e.g. location, a specific project, a faculty member, etc.), be sure to mention them.

In terms of your motivation, be specific! Don’t write: “I’ve wanted to do a PhD in CS since I was six years old.” We don’t trust that six-year-olds make good career decisions. If you write “I have always found AREA X fascinating,” explain why.

Letters of Recommendation

The two most important factors of a recommendation letter are: 1) select someone who knows you well, and 2) select someone who knows how to write a letter.

First, it’s tempting to ask Professor X. to write a letter for you because they are a well-known person in the field. While we can better contextualize letters from people we know, it’s only helpful if the letter contains meaningful information. If Professor X. writes, “I’ve met the applicant a few times and they seem sharp,” that’s not useful information. It’s more important to select someone who knows you well and can discuss your achievements in detail.

Second, your letter writer should know how to write a letter. Academic research programs look for different things than a company. We often read letters from work supervisors that say nice things, but don’t speak to the qualities we find most important.

Of course, it’s a balance. You want someone who knows you well, but they still need to know how to write a good letter of recommendation.

We understand that three letters are a lot, especially for an undergraduate applying directly to a PhD program. We don’t expect each candidate to have three amazing letters. Your choices should be about balance: you want people who know you well, can write good academic letters, and know the research field. Use your choice of your three letter-writers to create this balance.

There isn’t much you can do about your grades—you have the grades you have. However, we do not use any grade cutoffs or thresholds in admissions. We want to see that you did well and excelled in whatever program you were in. Did you push yourself to take upper-level classes? Did you do well in the classes most directly related to your research area? If you have special circumstances that explain some of your grades, please include a description of them in your statement.

The Whiting School of Engineering does not require GRE General Test scores for applications to our PhD programs.

TOEFL or IELTS

Non-native English speakers must take the TOEFL or IELTS exams. Details on accepted exams, scores, and exceptions to this requirement can be found here .

Application Tips

There are many helpful guides for PhD applications. Here are a few we recommend:

• How to be a Successful PhD Student (co-authored by our own Mark Dredze )
• What Readers Look for in a Statement of Purpose
• Student Perspectives on Applying to NLP PhD Programs
• A Survival Guide to a PhD

Application Deadlines

Application Deadline:

The deadline for fall is December 15th. (No recruiting for spring admissions.)

The application will be available for submission on or around August 15.

Vivien Thomas Scholars

The Vivien Thomas Scholars Initiative (VTSI) is an endowed fellowship program at Johns Hopkins for PhD students in STEM fields. It provides full tuition, stipend, and benefits while also providing targeted mentoring, networking, community, and professional development opportunities. Students who have attended a historically black college and university or other minority serving institution for undergraduate study are eligible to apply. To be considered for the VTSI, all application and supplementary materials must be received by December 1, 2021.

Department of Computer Science

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The Ph.D. in Computer Science aims to build the next generation of scholars in computer science research. At GW, doctoral students can expect to work closely with a faculty advisor in their chosen research area to create a curriculum plan and guidance for the doctoral dissertation. Students have the opportunities to teach introductory-level courses to undergraduates, present conference papers, and work with faculty on research grant applications.

With its unique location of Washington, D.C., GW maintains access and connections to one of the highest concentrations of tech companies in the country, as well as research-granting federal institutes, including the National Institutes of Health (NIH), NASA , National Institute of Standards and Technology and the Naval Research Laboratory . 

For Prospective Students:

Admissions requirements.

• If an applicant has obtained a master’s degree, a minimum grade point average of 3.5 (on a scale of 4.0) is required.
• If an applicant has only obtained a bachelor’s degree, the minimum grade point average must be a 3.3 (on a scale of 4.0).
• Completion of two math courses beyond pre-calculus.
• Strong academic background that includes courses in structured programming language, discrete structures and data structures.
• Successful submission of online application form, exam scores and other documents as outlined in the admissions requirements .

Faculty Advisor & Research Area

We strongly recommend that prospective doctoral students determine a faculty member in the department with whom they would like to work, as well as the research area of interest.

Top research areas of the department:

• Algorithms and theory
• Computer architecture, networks, parallel and distributed computing
• Computer security and information assurance
• Database and information retrieval systems
• Machine intelligence and cognition
• Multimedia, animation, graphics and user interface
• Software engineering and systems

Download Faculty & Research Factsheet (PDF)

For Current Students: 

The general requirements are stated under School of Engineering, Doctoral Program Regulations . 

Program Requirements

Relevant Forms

• Preliminary examination form
• Proposal defense report form
• Final examination approval form
• Dissertation completion form
• Additional forms and resources from SEAS

PhD Course Guidelines:

PhD students must work with their advisors to develop a program of study that meets the following requirements.

• For direct Ph.D. degree students: 54 credit hours (minimum of 42 credit hours of course work available for graduate credit and minimum of 12 credit hours of dissertation research credits (CSCI 8999)) are required. Additionally, a student should continue to enroll in Continuing Research - Doctoral (SEAS 0940) until their dissertation is completed.
• For post-Master’s Ph.D. students: 18 credit hours of course work available for graduate credit and 12 credit hours of dissertation research credits (CSCI 8999) are required. Additionally, a student should continue to enroll in Continuing Research - Doctoral  (SEAS 0940) until their dissertation is completed. 
• A maximum of 15 credits outside of the department for direct Ph.D. students; a maximum of 9 credits outside of the department for post-Master’s Ph.D. students.
• Algorithms and theory;
• Software and systems
• See details in the Preliminary Examination section below. 

Preliminary Examination

Failure of full-time students to pass the preliminary examination by the end of the fourth semester will lead to dismissal from the program.

Students who register for 6 credits or fewer in three consecutive semesters are part-time. Part-time students are required to pass the preliminary examination within their first three years, or 30 credits, of enrollment in the PhD program. Failure to do so will result in dismissal from the program.

To demonstrate competency, students may take one course in each of the following areas:

• Algorithms and theory: CSCI 6212 Design and Analysis of Algorithms or CSCI 6311 Theory of Computation
• Software and systems: CSCI 6221 Advanced Software Paradigms, or CSCI 6431 Computer Networks, or CSCI 6461 Computer System Architecture

Competency is demonstrated in one of two ways:

• By completing the course with a minimum grade of A-; or,
• By taking only the written, in-class examinations in the course. With this option, students must pass all exams given during a semester, earning a minimum grade of A- in each. 

Students who prove, via their official transcript, that they earned the requisite grades as part of their master’s degree may apply that result to the preliminary exam requirement. 

Students must submit a Preliminary Examination Form to the Department of Computer Science after completing the requirements for the preliminary exam. 

Publication Requirements

Students must have at least one peer-reviewed conference or journal paper accepted for publication at the time of the dissertation defense.

As a guideline, students are expected to have at least two or three conference or journal papers accepted for publication by the time of their dissertation defense, and the material from those papers should be the core of the dissertation.

Dissertation

Dissertation advisor and co-advisor(s).

Every PhD dissertation must be supervised by a faculty advisor who must be (1) a regular full-time faculty member of GW with a primary or secondary appointment in the CS Department, or (2) a research faculty member of the CS Department. Besides the dissertation advisor, a PhD student may have one or more co-advisor(s), who may be full-time or part-time faculty at GW, or professionals from outside the university. Co-advisors are expected to hold a terminal degree.

Forming a dissertation committee

• The dissertation committee must consist of at least three members, including the major advisor. Additional advisor(s) and co-advisors are optional and additional to the three members.
• The committee must have a presiding chair who is a regular full-time faculty member whose primary appointment is in the Department of Computer Science. The committee chair may not be the student's research advisor or co-advisor.
• Faculty with secondary appointments in the Department of Computer Science are not considered regular full-time faculty members in the Department.
• At least one member of the committee must be an external reviewer. The external reviewer must hold a doctoral degree. They may not be a research advisor or co-advisor of the student. They should have a primary appointment in another GW department or outside the University.
• The dissertation committee must be approved by the Chair of the Department of Computer Science.
• The committee membership is normally the same for the dissertation proposal examination and the dissertation defense. However, the membership may change with the approval of the advisor and department chair.

Dissertation proposal defense

• The defense may not take place before the student has passed the preliminary examination.
• The student’s advisor must approve the scheduling of the dissertation proposal defense.
• The student submits a written proposal, in the style of a dissertation, to the members of the dissertation committee. The proposal should contain preliminary results.
• The dissertation committee evaluates the proposal and conduct an oral examination of the student. The committee conveys its recommendation of pass/fail to the Department of Computer Science.
• A proposal defense report should be filed.  

Dissertation defense

• The dissertation defense may not be scheduled before the student has passed the dissertation proposal defense.
• The student’s advisor must approve the scheduling of the dissertation defense.
• The student submits a written dissertation to the members of the dissertation committee, normally two or more weeks in advance of the defense. The writing should follow the dissertation writing guidelines .
• The committee evaluates the dissertation and conducts an oral examination of the student. The committee conveys its recommendation to pass or fail to the Department of Computer Science.
• The final examination approval form and the dissertation completion form should be filed.

University Graduation and Scholarship Requirements

Students are responsible for knowing the University’s graduation and scholarships requirements. Consult the University Regulations section of this Bulletin. Students should consult the department for additional information and requirements.

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PhD in Computer Science

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The PhD is the primary research degree that can be taken in the Department of Computer Science and Technology. The Cambridge PhD is a three to four-year full-time (five to seven-year part-time) programme of individual research on a topic agreed by the student and the Department, under the guidance of a staff member as the student's supervisor. 

All research students are admitted to read for the PhD degree on a probationary basis and will be registered for the Certificate of Postgraduate Study (CPGS) in the first instance. During this year students may do some additional coursework and will write a research report that is likely to form the foundation of the eventual PhD thesis. The CPGS will involve four components:

Research skills training

Practical work

Research report of no more than 10,000 words

Attendance at a research workshops and research seminars

At the end of the third term and on completion of the CPGS, students whose performance indicates that they would be able to complete a PhD in a reasonable time will be upgraded to PhD status. A student who is not upgraded to PhD status, and who has completed three terms of study, will normally be awarded the CPGS alone. They will not submit a thesis for the PhD degree.

There is an expectation that all research students will contribute to teaching in the department for which some training will be provided. Research students will submit a log - or tally-sheet - of teaching activities annually at the end of June. 

Students are expected to complete the substance of their research by the end of their third year, submitting their thesis then or within a few months.

Applicants wishing to apply to undertake a PhD on a part-time basis should refer to the Department's admissions advice for potential part-time students.

The Postgraduate Virtual Open Day usually takes place at the end of October. It’s a great opportunity to ask questions to admissions staff and academics, explore the Colleges virtually, and to find out more about courses, the application process and funding opportunities. Visit the  Postgraduate Open Day  page for more details.

See further the  Postgraduate Admissions Events  pages for other events relating to Postgraduate study, including study fairs, visits and international events.

Key Information

3-4 years full-time, 4-7 years part-time, study mode : research, doctor of philosophy, department of computer science and technology, course - related enquiries, application - related enquiries, course on department website, dates and deadlines:, lent 2024 (closed).

Some courses can close early. See the Deadlines page for guidance on when to apply.

Michaelmas 2024 (Closed)

Funding deadlines.

These deadlines apply to applications for courses starting in Michaelmas 2024, Lent 2025 and Easter 2025.

Similar Courses

• Advanced Computer Science MPhil
• Machine Learning and Machine Intelligence MPhil
• Research in Agri-Food Robotics EPSRC CDT PhD
• Biological Science (Babraham Institute) PhD
• Biological Sciences (Developmental Biology) by advanced study MPhil

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Doctor of Philosophy in Computer Science

Program description.

The graduate programs in computer science offer intensive preparation in design, programming, theory and applications. Training is provided for both academically oriented students and students with professional goals in the many business, industrial and governmental occupations requiring advanced knowledge of computing theory and technology.

Courses and research opportunities are offered in a variety of subfields of computer science, including operating systems, computer architecture, computer graphics, pattern recognition, automata theory, combinatorics, artificial intelligence, machine learning, database design, computer networks, programming languages, software systems, analysis of algorithms, computational complexity, parallel processing, VLSI, virtual reality, internet of things, embedded and real-time systems, computational geometry, computer vision, design automation, cyber security, information assurance and data science.

The University maintains a large network of computer facilities including specialized computers for research within the program. In addition to computer science faculty, many other individuals at the University are involved in computer-related work in the physical and social sciences and in various areas of business and management. Computer science students with an interest in these important application areas may have opportunities to consult and work with talented faculty from a wide range of disciplines.

Career Opportunities

Graduates of the program seek academic positions at universities, as well as positions as researchers, senior software engineers, data scientists. Graduates often become industry experts in fields like cyber security, artificial intelligence, machine learning or natural language processing.

Marketable Skills

Review the marketable skills for this academic program.

Application Requirements

Test score required:  Yes

Deadlines:  University  deadlines  apply.

OTHER APPLICATION REQUIREMENTS

Admission Option One

• Master’s degree in computer science or its equivalent
• GPA of at least 3.5
• GRE revised scores of at least 308, 153, 155 and 4 for the combined, verbal, quantitative, and analytical writing components, respectively, are advisable.

Admission Option Two

• A BS degree in related area that includes two semesters of calculus and linear algebra
• GPA of at least 3.5 in the last 60 semester credit hours
• GRE revised scores of at least 315, 156, 159 and 4 for the combined, verbal, quantitative, and analytical writing components, respectively, are advisable.

Applicants are admitted on a competitive basis.

Contact Information

Shyam Karrah  Email: [email protected]

Dr. Ovidiu Daescu Interim Head Department of Computer Science Email: [email protected] Office: ECSS 3.904

Erik Jonsson School of Engineering and Computer Science The University of Texas at Dallas, ECW41 800 W. Campbell Road Richardson, TX 75080-3021 [email protected]

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Since the department's founding in 1968, faculty members have made pioneering contributions to fundamental and interdisciplinary fields of computing. Today, the department is a research and education leader in computation, information, and digital media, offering innovative environments for study and research.

Department newsletter: Fall 2021

It’s been an exciting year for USC’s Department of Computer Science! See some of our faculty and student highlights, learn more about our new hires and research funding awards in this handy fact sheet.

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Jingbo Wang PhD in Computer Science

What’s the best piece of advice you’ve ever been given?

What do you consider your greatest accomplishment?

What's your favorite impulse purchase from the past 12 months?

Nintendo switch! During COVID, most of the time, we have to stay at home. Playing some games (e.g. animal crossing) on Nintendo switch is really relaxing

Please describe a little about your research and what excites you about it.

If you could choose any other profession outside of engineering or computer science, what would it be? 

I think I would like to pursue J.D. or LL.M in law school. For some of the code-based laws, it is well suited to apply formal methods and logic to represent them. Researchers have proposed a default logic to formalize the federal tex code and its accompanying regulations. What I’m currently doing is applying the logic to formalize the behavior of the software. In the future, I wish I could use that to formalize code-based laws, to detect ambiguities and drafting errors.

What are some factors that helped you decide to pursue your PhD at USC?

There are so many reasons:) First, the professor I want to work with is at USC. Second, there are many PL/SE researchers in USC and we could discuss, collaborate in many possible ways. The atmosphere here is really motivating. Third, USC has so many female clubs (e.g. WinCC, WiSE) where we could learn from each other’s experiences and try to encourage more females in the STEM area. Fourth, USC provides many valuable classes such as public speaking, creative thinking, arts performance and etc. It really broadens our horizons in addition to our own expertise. Last but not least, LA is such a special city with palm trees, skateboarding teens, oddball bohemians, and the occasional movie star. You will fall in love with it once you come here.

If you were to recommend to an incoming student 3 places to go in California/Los Angeles, what would they be?

Griffith observatory, Universal Studios, Getty center

What is a memory you'll cherish about your time at USC?

There are so many unforgettable memories at USC. The farmer’s market outside Leavey library, annual conquest rally, birthday celebrations for our lab-mates, and hanging out together in USC Village.

What's one thing about you that might surprise me?

Although I give public presentations in the premier conference and make friends with other researchers, I am a typical introvert and I dislike social activities. When attending the conference, people are expected to interact with each other over few days. To be frank, I enjoy talking with people and introducing my research. However, none of these could compare favorably to solitary. I always spend a lot of time learning and reflecting in solitude. It’s more like a meditation where I could relax and talk with myself.

What are your plans after graduation?

I plan to stay in academia and look for faculty jobs or other research-related jobs.

Hometown (city, country):

Nanyang, China.

Personal Website (if any):

http://scf.usc.edu/~ jingbow/

Faculty Advisor:

Prof. Chao Wang.

Kegan Strawn PhD in Computer Science

I subscribe to the "next right step" advice. Life can be overwhelming at times, especially during your studies, and focusing on the next right step rather than the entire mountain you are trying to hike up has really helped me every day.

I  come from a family where no one has been in academia and I was not exposed to anything close to it growing up. Research, and even college, felt like this scary gated community that only a certain few could participate in and I'm very grateful to those in my undergraduate studies who helped open the gate for me and showed me that anyone can do this. Don't get me wrong, I have many privileges in my life, but I'm very proud to be here at USC and working hard among some very smart peers every day. 

Last week I bought an LA Dodgers hat at the game against the Giants. I think this means I can officially say I live here now.

I work in multi-robot coordination and collaboration. I'm very interested in how robots can work together with other robots and humans as part of a team to help improve our lives. It's slightly different from the majority of current work that is about training a robot to beat us at a certain game or to replace a job completely. I spend a lot of my time thinking about how we can improve the algorithms they use and the way they learn to work together and I find it incredibly fun and rewarding work.

If you could choose any other profession outside of engineering or computer science, what would it be?

I always wanted to be a veterinarian when I grew up. I love animals and find biology and genetics fascinating. So, I think I still want to be a vet when I finally grow up.

If they are looking to live somewhere I highly recommend the Culver City area. For things to see, I really like the Getty Center for not only the art but the cool architecture and outdoor garden. I also love cruising up and down the pacific coast highway and going to any of the beaches (although Hermosa beach down south is my favorite). Finally, I'd recommend some Korean BBQ in Koreatown. 

I only applied to drama colleges for college. I was fully expecting to only ever be in LA for acting, but now I'm here for my Ph.D. working in computer science and robotics. Life has a crazy way of working out!

Currently, I am interested in continuing in academia with a postdoctoral position.

Fort Collins, Colorado, USA.

https://sites.google.com/view/ kegan-strawn

Professor Nora Ayanian

Kushal Chawla PhD in Computer Science

What’s the best piece of advice you’ve ever been given?

One should never judge their own or someone else’s decisions based on the outcomes (that is, in hindsight). That’s just unfair! Instead, think about whether the decision made sense, given the situation you were in. If you are in a similar situation again, how can you make a better call?

That has to be the network of friends and colleagues that I could build from a variety of professional experiences in both academia and industry. Life is a bit easier with folks you can always turn up to for some advice and of course, for referrals!

Minion-shaped slippers with button eyes that move when you walk.

I am currently working on enabling human-machine negotiations in natural language such as in English. Think about buyer-seller price negotiations or salary negotiations. Automated systems that negotiate with humans can be really helpful in advancing conversational AI and for teaching social skills to humans. Most practical systems in this space are based on restrictive communication protocols such as a predefined menu of options. Instead, I am trying to incorporate more natural means of communication such as language so that these systems can be more useful in the downstream applications. This area opens up exciting avenues for interdisciplinary research between NLP, Affective Computing, and Psychology. For a glimpse of what I do, here is a TechXplore blog that covers our recent work published at NAACL-HLT 2021: https://techxplore.com/news/2021-05-casino-campsite-based-dialogs- automatic.html

A full-time host for grand cultural events! I just love the job and the feel that comes with it! Even now, I grab such opportunities with both hands.

First and foremost, my interactions with the lab that I am joining. I would definitely recommend that to all the prospective students. Secondly, the ever-increasing research opportunities and a helpful environment over here at USC. Lastly, it would be unfair if I don’t include this but the nice LA weather was always there at the back of my mind.

- Weekend getaway at Big Bear - Manhattan beach - Hikes in Malibu

I am a part of a religious organization at USC called the Bridges International. In Fall 2019, we went to Big Bear for a weekend, in a group of nearly 30. We rented out two huge houses near the lake, danced and sang songs from different cultures around the globe, and went for a hike! Amazing experience!

I have an OCD of repeatedly checking the locks and always making sure that everything is locked. It is so bad that once, during my undergrad, I preferred to calmly lock my door first, when everyone else was vacating the building due to a strong earthquake. As a side note, I later got to know that my friend ran with a laptop in her hand: the most expensive stuff that she could find in her room. People have weird priorities!

I am keeping it wide open for now, although I am slightly inclined towards joining the industry again, given my previous experience as a full-time researcher at Adobe for a couple of years.

Delhi, India.

https://kushalchawla.github.io/

I am jointly advised by Gale Lucas and Jonathan Gratch at ICT, USC.

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The Department of Computer Science and Technology will offer a part-time route to the PhD Degree with effect from October 2022. 

Part-time structure

The Department of Computer Science and Technology could offer a part-time route to the PhD. At present, the University allows a part-time route which is 60% or 75% of a fulltime PhD route for which the minimum number of terms:

 60% route -15 terms minimum; maximum number of terms for a part-time student is 21 terms.

 75% route - 12 terms minimum; maximum number of terms for a part-time student is 16 terms.

The requirements for the probationary CPGS in Computer Science will be spread across two years with the first-year report due near the end of the fifth term (i.e. end of March for a Michaelmas admittee), and the registration viva occurring in the sixth term (Easter term). The Department expects the completion of the required 12 units from the Researcher Skills Programme across two years. Part-time students are also encouraged to spend one term full-time in the first year of the programme and that students will be in residence in Cambridge during that time.

After successful registration for the PhD Degree, part-time Ph.D. students are expected to have between 2 and 4 meetings with their supervisor per term for at least a further ten terms. They are expected to spend an average of three weeks each term in the Department with a minimum of 45 nights p.a. in residence.

Requirements for a part-time PhD applicants in Computer Science and Technology

• The proposed topic needs to be suitable for study over a minimum of 12 or 15 terms (75% or 60% route respectively) and a maximum of 16 or 21 terms (75% or 60% route respectively) . Applicants will need to provide a schedule of the research over the first few years. 
• If a supervisor identifies a potential student and a topic as being possibly suitable for part-time study, an initial interview report form must be sent to the PhD Applications Panel for consideration.
• Potential supervisors should invite the Chair of the PhD Applications Panel or a deputy to attend the formal interview.
• As well as consideration by the PhD Applications Panel, the interview report will be considered by, and a decision approved by, the Degree Committee. The approved form will also be loaded to the applicant portal for consideration by the Postgraduate Admissions Office.
• The proposed supervisor must be able to supervise a part-time Ph.D. for at least the minimum 15 terms. This means that supervisors on short-term contracts, or those due to retire within seven years of a part-time student being admitted, will not be eligible to supervise. Those who are due to take sabbatical leave should consider alternative supervision arrangements.
• Applicants should be aware that there is no obligation on supervisors to accept applicants who wish to be admitted as part-time students.
• The student must live close enough to Cambridge, or be able to spend enough time in Cambridge during the first two years, to be able to participate, as much as possible, in research group seminars, reading groups and other activities.
• The student and supervisor will sign an agreement about how often the student will be in the department. This might be, for example : 2 x 8-hour days per working week per term, or 3 x 1-week per term, plus 40% of time in the research term (1 July to 30 September).
• Most CST Research Skills courses are available remotely. For research themes’ group meetings and seminars, physical presence in the department is preferred.
• The student will be required to provide a letter from the employer (if the student is employed) confirming that they may have time off to attend the University as required for the duration of the course. Applicants are required to upload a part-time attendance Declaration to their application once approved for admission.

Updated May 2024

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Carnegie Mellon University School of Computer Science

Scs graduate admissions overview.

Thank you for your interest in graduate studies at Carnegie Mellon's School of Computer Science! We  offer a wide range of professional and academic  Ph.D.  and master's programs  across our seven departments. Admissions and requirements vary by program and are determined by the program's home department. You can apply to up to three of our Ph.D. programs and any of our master’s programs.

Important Information for Programs Beginning in Fall 2025

Note: Some of our programs follow different deadlines, see application information and links below for more information.

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SCS Graduate Admission Applications

Use the links below to apply to the program(s) of your choice., scs doctoral programs.

Ph.D. Application for Computer Science and Human-Computer Interaction

Ph.D. Application for Computational Biology, Language and Information Technologies, Machine Learning, Societal Computing, Software Engineering and Robotics

Note : To apply to the doctoral track in Algorithms, Combinatorics and Optimization (ACO) or in Pure and Applied Logic (PAL) ,  you must apply to the Ph.D. program in Computer Science . You should state in the first paragraph of your Statement of Purpose that you are interested in either ACO or PAL. If admitted, you will be allowed to choose that program during your first year.

Master's Programs in Computational Biology

Master of Science in Automated Science: Biological Experimentation Application

Master of Science in Computational Biology Application

Master's Programs in Computer Science

Master of Science in Computer Science Application

Master's Programs in Human-Computer Interaction

Master of Human-Computer Interaction Application Note: MHCI has a deadline that has yet to be determined.

Master of Educational Technology and Applied Learning Science Application

Master of Science in Product Management Application Note : MSPM has rolling admission for spring.

Master's Programs in Software and Societal Systems

Master of Software Engineering  For applicants with two or more years of software engineering experience in industry

Master of Software Engineering - Embedded Systems Application For applicants with less than two years of software engineering experience

Master of Software Engineering - Scalable Systems Application For applicants with less than two years of software engineering experience Note : The three programs above — MSE, MSE-ES, and MSE-SS — are not following any early deadlines and the application fee is $100.

Master of Science in Information Technology - Privacy Engineering Application

Master of Software Engineering Online Application Note : MSE Online follows a different deadline schedule.

Master's Programs in Language Technologies

Master of Computational Data Science Application

Master of Science in Artificial Intelligence and Innovation Application

Master of Science in Intelligent Information Systems Application

Master of Science in Language Technologies Application

Master's Programs in Machine Learning

Master of Science in Machine Learning Application

Master's Programs in Robotics

Master of Science in Computer Vision Application

Master of Science in Robotics Application

Master of Robotic Systems Development Application

Programs With Joint/Multiple Applications

Machine Learning Joint Ph.D.: S tudents interested in an ML-Joint Ph.D. should first apply to the Ph.D. program that best aligns with their research interests. Once you are enrolled in one of the participating Ph.D. programs and have passed 10-715, 10-705 and 10-716, there is a lightweight  application to apply  for a joint Ph.D. in machine learning. 

MD/Ph.D. in Computational Biology : Students must apply via the  Medical Scientist Training Program . More information is available on the  Medical Scientist Training Program website .

Interdisciplinary Programs in the Center for the Neural Basis of Cognition:  Students should apply to their primary SCS Ph.D. program but must also apply to the  CNBC Graduate Training Program . More information can be found on the  CNBC website .

WPI - Computer Science Department, PhD Proposal Presentation, Christopher Micek " Mindful Machines: Enabling HCI Research Exploring Novel Brain-Driven Interaction Paradigms for Learning and Collaboration"

Mindful Machines: Enabling HCI Research Exploring Novel Brain-Driven Interaction Paradigms for earning and Collaboration

Christopher Micek

PhD Candidate

WPI – Computer Science Department 

Date:  Friday, August 9th, 2024

Time:  3:00 pm – 4:00 pm

Location : Zoom:  https://wpi.zoom.us/j/98970971021

Committee Members :

Advisor: Prof. Erin Solovey, WPI – Computer Science

Prof. Lane Harrison, WPI – Computer Science

Prof. Yunus Telliel, WPI – Humanities & Arts (External Committee Member)

Prof. Felix Putze, University of Bremen – Mathematics & Computer Science (External Committee Member)

 With advances in the capabilities and affordability of brain sensing technologies, brain data is increasingly being integrated as input into interactive systems. Such data can give insight into the cognitive and affective states of users, augmenting their capabilities and enriching interactions, as well as informing user-centered design and evaluation of innovative interfaces. 

However, there is a dearth of user-friendly tools supporting the development of brain-computer interfaces, which typically requires a high level of time and expertise. The aims of this dissertation are to develop and evaluate such tools and methods to make working with brain data accessible, and to demonstrate the utility of brain signals in novel interaction paradigms for learning and collaboration.

DEPARTMENT(S):

• Equity & Inclusion

PhD student aims to improve AI for underserved languages and communities

Hellina Hailu Nigatu always loved math and physics – really any field that let her calculate things. Then she found computer science. By the time she'd started her PhD at UC Berkeley, she saw how computing skills could address a range of issues from healthcare to women's rights.

She learned in classes about concepts in Natural Language Processing and large language models developed in English. But Nigatu, who is Ethiopian, found that most of the methods she learned wouldn’t work in other languages she knew. The data didn’t exist on the internet to build chatbots for the Tigrinya language, like the ones already changing how English speakers live and work. The safeguards blocking some harmful content online weren’t effective for Amharic-speaking users.

“This is what happens when you have diversity in computer science,” said Nigatu, who is starting the fourth year of her doctorate program. “Almost all of my projects are inspired by personal experience.”

“I could be an English speaker who improves machine translation, speech recognition and whatever other technology in Amharic by  looking at performance on some evaluation metric,” she said. “But if I did not speak this language, if I was not from Ethiopia, if I was not impacted by this, I wouldn’t have the context to understand the nuanced problems that go beyond automatic metrics.”

The artificial intelligence boom is rapidly transforming modern life. But with a lack of diversity in who informs and develops these technologies and the disparities in the existing data being used, these tools could cement and exacerbate global inequalities.

Nigatu is an up-and-coming expert combating that risk through research and mentorship. She hopes to develop tools that are informed by and useful for communities, including her family and friends, who speak languages that have little available data online.

Preserving languages and cultures that have less data online

Nigatu graduated from Addis Ababa University with a bachelor’s of science in electrical and computer engineering. She graduated from Berkeley with a master’s of science in computer science and is being advised for her PhD by Berkeley Department of Electrical Engineering and Computer Sciences’ Sarah Chasins and John Canny .

The barriers Nigatu has faced in applying Natural Language Processing tools and techniques to languages with less data available – or low-resourced languages – inspired one of her latest research papers. Early in her doctorate program, she decided to build language models in Amharic and Tigrinya. But when she went to Wikipedia, a common source of data for language processing work, she found there weren’t enough entries for either language to develop those models. The entries that did exist were often not high quality enough to use, either.

Her recent paper from the ACM Conference on Human Factors in Computing Systems – “ Low-Resourced Languages and Online Knowledge Repositories: A Need-Finding Study ” – looked for an answer to why that hurdle existed. Nigatu and co-authors analyzed Wikipedia forum entries by experienced contributors and conducted interviews with novice contributors to Wikipedia for three languages – Amharic, Tigrinya, and Afan Oromo.

They found several intersecting challenges that made it difficult for people to add entries to the platform in these languages. Wikipedia contributors struggled with the design of the platform or the lack of language-support tools like keyboards for languages that weren’t based in Latin. They also ran into challenges due to socio-political issues, such as the lack of scholarly work freely accessible on the internet that they could cite in their entries.

The dearth of data on currently recognized online knowledge repositories like Wikipedia presents major risks, Nigatu said. These platforms are being used to develop next generation tools that will be foundational to how we live our lives moving forward. The platforms are already preserving and sharing information and cultural values in higher-resourced languages like English, but aren’t offering equally useful or accessible data for other languages, she said. 

“We should be building from the ground up with community values in mind.”

“We should be building from the ground up with community values in mind, so that we preserve these languages and these identities without expecting them to adapt to the default,” said Nigatu. These platforms must “serve their needs” and not exploit them or their data, she said.

Improving the safety of the online experience

Nigatu has also found research questions through her own lived experiences. She noticed that when she searched for benign terms in Amharic on YouTube, she’d receive policy-violating, pornographic videos as results. When she dug deeper, she found this was a broader pattern for Amharic search results on the platform. She turned her discovery of this issue into a paper.

Niagatu and co-author Inioluwa Deborah Raji collected data from, and conducted interviews with, users of the platform centered on the YouTube results for Amharic searches. In their paper “ I Searched for a Religious Song in Amharic and Got Sexual Content Instead”: Investigating Online Harm in Low-Resourced Languages on YouTube ,” they found that content moderation was a big problem. Very few human content moderators focus on any non-English language, and automated content moderation doesn’t work well for low-resourced languages.

They also found people posting on YouTube used techniques to evade moderation, like using “doctor” or medical terms in their channel names in order to seem like they were offering health advice. And by analyzing the comments, they found that migrant workers located in Middle Eastern countries seeking medical advice were often tricked into clicking on pornographic content. Amharic users interviewed for the paper said they felt disempowered and devalued.

“This project showed that when we ignore a huge population in how we design and how we build technologies, the result is that these populations are disproportionately burdened with the harms,” said Nigatu of the paper published in Proceedings of ACM Conference on Fairness, Accountability, and Transparency .

“When we ignore a huge population in how we design and how we build technologies, the result is that these populations are disproportionately burdened with the harms.”

But for Nigatu, this project also highlighted something else. As she was working on this paper, she had to overcome significant pushback and questions from others about whether this was a problem and whether there was real harm being done here. It made her question whether to tackle the paper at all. She credits Raji for encouraging her to continue.

“When I say ‘online harm,’ people are like, ‘Oh, did it lead to genocide? Did people die from it?’ And I'm like, ‘I mean, harm doesn't have to get to that stage for it to be harmful,’” said Nigatu. “The standards that we have for what's acceptable to certain communities and what's not is very, very different.”

Expanding the field moving forward

Nigatu is already onto her next project. In June, she received a diversity, equity and inclusion scholarship from the ACM Conference on Fairness, Accountability, and Transparency. 

Using this recognition, she will work to improve machine translation for low-resourced, Ethiopian languages. She will also fund and mentor female students from Ethiopia to work on that research with her. This builds on past mentorship she’s offered to Ethiopian women in the computer science field.

“I know how hard it was for me to try to do research when I was there, so I do whatever I can do to try to bridge that gap,” Nigatu said.

While technology is rapidly advancing, diversifying who creates computing tools will take time. In the meantime, she hopes researchers will speak with members of underrepresented communities to hear their experiences and insights.

She feels the responsibility of being an Ethiopian female researcher every day. When she interviewed with Chasins to be her PhD advisor at Berkeley years ago, Chasins asked what would get Nigatu out of bed on the mornings she was too exhausted to do the work. Nigatu’s answer was simple.

“I don't have the luxury of saying, ‘Oh, I can’t do it today,’ because it's practically me. I am the person who's at the end going to be using these technologies. It's my friend. It's my sisters. It's everyone that I'm close to,” she said. 

“I pull a lot of the motivation for my work from my personal experience and from the experiences of those around me,” Nigatu said. “It keeps me going."

For Media Inquiries

[email protected]

Meet the Expert

Hellina Hailu Nigatu is a computer science PhD student at UC Berkeley. (Photo courtesy of Hellina Hailu Nigatu)

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Aug 6 (Tue) @ 11:00am: ”Millimeter Wave Power Amplifiers: Embedding Techniques and Rapid Optimization,” Everett O'Malley, ECE PhD Defense

Communication systems in millimeter-wave bands promise unprecedented access to high data rates in wireless links. Power amplifiers account for a large fraction of transmitter power dissipation. Consequently, increasing the efficiency of power amplifiers is critical for improving the efficiency of transmitters. The design of power amplifiers, and circuit design in general, consists of an exploration through the permutations of circuit topologies. This work offers two different methods for searching the myriad possible designs.

First, we describe an automation approach that we apply to designing D-band power amplifiers. We generated circuit models from EM-simulation and loadpull. The optimization then proceeds from these circuit models, without any further need to employ time consuming harmonic balance or electromagnetic simulations. As a result, the per iteration time cost of our method is much faster than in similar works, which used Bayesian optimization techniques to reduce the number of iterations used. We use the improved optimization efficiency to investigate 49 matching-network candidates for each stage of four stage amplifiers. We applied the optimization approach for three different amplifiers in two process-technologies. In all cases the optimization time was less than seven seconds. In measurement, the amplifiers achieve peak power added efficiency (PAE) between 13.6% and 15.5% with less than a 3% shift in peak PAE frequency from the 140 GHz design target. Measured output powers ranged between 14.5 and 14.9 dBm.

Second, we describe methods for designing gain-boosted amplifiers that simultaneously satisfy both gain matching and power matching conditions. Gain-boosted amplifiers are popular in literature at high fractions of fmax, but the usual design equations assume gain matching, which may not present the core device with a load impedance that results in good power performance. We identify all possible port-parameter embedding networks that result in the canonical unilateral form, parameterized in terms of the load impedance presented to the core amplifier. The parameterization of unilateralizing embedding networks is then used to find the embedding networks that simultaneously meet the gain matching and noise matching conditions, thus achieving minimum noise measure. A power amplifier design example is given at 2.5 GHz. We describe an embedding-network synthesis approach based on identifying the directional coupler that must be equivalent to both the target 4-port embedding network and to the candidate design structure.

Everett O'Malley received the B.S. degree in electrical engineering and physics from Northeastern University, Boston, MA, USA, in 2018 and the M.S. degree in electrical engineering from the University of California, Santa Barbara, Santa Barbara, CA, USA, in 2020. Since 2018, he has been a Graduate Student Researcher with the University of California, Santa Barbara. His research interests include the use of feedback in mmwave amplifiers to improve noise and power  performance, and also machine learning approaches for mmwave integrated circuit design automation and optimization.

Hosted by : Professor James F. Buckwalter

Submitted by : Everett O'Malley <[email protected]>

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Graduate Certificates Courses & Policies

The Online Graduate Certificate from Penn Engineering Online is a for-credit credential that will produce an academic transcript and paper certificate. To earn a certificate, students can take a maximum of four (4) course units. Two of these four course units may be double-counted from your Penn Engineering graduate degree program.

Students may earn a maximum of two certificates. No course may be triple counted, i.e., counted for more than two credentials.

While most individuals will complete the Online Graduate Certificate program within one year, students may choose to extend their studies. In this case, all Certificate requirements must be met within a maximum of two years.

*Note: Degree students will receive first priority for course registration.

Computer Science Fundamentals Graduate Certificate Courses

One (1) Required Course

Introduction to Software Development

This course is an introduction to fundamental concepts of programming and computer science for students who have little or no experience in these areas. Includes an introduction to programming using Python, where students are introduced to core programming concepts like data structures, conditionals, loops, variables, and functions. Also provides an introduction to basic data science techniques using Python. The second half of this course is an introduction to object-oriented programming using Java, where students are introduced to polymorphism, inheritance, abstract classes, interfaces, and advanced data structures. Students will also learn how to read and write to files, connect to databases, and use regular expressions to parse text. This course includes substantial programming assignments in both Python and Java, and teaches techniques for test-driven development and debugging code.

Pre-Requisites

No Pre-Requisites

Three (3) courses from the following list:

Mathematical Foundations of Computer Science

This course introduces students to math concepts that form the backbone of the majority of computer science. Topics covered include sets, functions, permutations and combinations, discrete probability, expectation, mathematical induction, and graph theory. The goal of the course is to ensure that students are comfortable enough with the math required for most of the CIS electives.

There are no college-level prerequisites for this class. However, reviewing the algebra learned in high school will be very useful. No prior programming background is expected nor will this course assign any programming exercises.

Introduction to Computer Systems

This course provides an introduction to fundamental concepts of computer systems and computer architecture. Students learn the C programming language and an instruction set (machine language) as a basis for understanding how computers represent data, process information, and execute programs.

This course does not have prerequisites, but CIT 5910 Introduction to Software Development is a co-requisite.

Data Structures & Software Design

This course focuses on data structures, software design, and advanced Java. The course starts off with an introduction to data structures and basics of the analysis of algorithms. Important data structures covered include arrays, lists, stacks, queues, trees, hash maps, and graphs. The course also focuses on software design and advanced Java topics such as software architectures, design patterns, and concurrency.

Students in this course are expected to have completed or waived CIT 5910 Introduction to Software Development.

Computer Systems Programming

This course is a continuation of CIT 5930 and introduces students to fundamental concepts in computing systems. The course is divided into two parts. The first half of the course introduces important concepts in modern operating systems: processes, scheduling, caching, and virtual memory. The second half of the course provides an introduction to fundamental concepts in the design and implementation of networked systems, their protocols, and applications. The course will use the C program language, and will develop your knowledge on C system calls, and libraries for process/thread creation and manipulation, synchronization, and network communication.

Algorithms & Computation

This course focuses primarily on the design and analysis of algorithms. It begins with sorting and searching algorithms and then investigates graph algorithms. In order to study graph algorithms, general algorithm design patterns like dynamic programming and greedy algorithms are introduced. A section of this course is also devoted to understanding NP-Completeness.

CIT 5920 | Co-requisite: CIT 5940 (Taking concurrently is allowed but taking beforehand is preferred)

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Graduate Program 2024 - Computer Science

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AI Job Summary

About the Graduate Program:

Your ambition is to shape the digital future. Your goal is to continuously grow with engaging tasks. Your passion is to gain new experiences. At Tata Consultancy Services (TCS), we are looking for motivated talent like you.

At Tata Consultancy Services (TCS), we are currently recruiting for our IT Graduate Program in Australia commencing mid to late August 2024. Successful graduates will join the TCS team in a trainee role supporting various functions on real projects.

TCS is fueling growth and transformation by leveraging innovative technologies, new thinking and breakthrough ideas to stay future-ready. TCS is looking for graduates to train and develop to be part of the transformation revolution which TCS leads around the world.

We want all of our graduates to be confident, inquisitive and ambitious. TCS promises to provide opportunities of competency building and enhancement through its structured Initial Learning Program, focusing on a mix of technical and business skills and this is followed by our continuous learning program that will equip them with skills and competencies to keep pace with the fast-changing world of technology.

TCS will further build your skills specific to the role and business. Thus, every successful graduate will have an understanding of our business values and culture, a dedicated mentor, on the job training and development tailored to the role and an introduction to TCS leading edge technologies.

We have varied streams available in:

• Data Analytics
• Cyber security (Identity access management Business analysts and Identity access Management Developers)
• Cloud technologies and Infrastructure Solutions
• Quality engineering through testing
• Digital technologies
• Application development (like business applications, mobile applications, UX/UI etc.) and maintenance
• Customer service (IT) 

What we’re looking for:

• Australian/New Zealand citizen and residents and full work right in Australia
• Bachelor’s degree or master's in computer science, Technology, Engineering or Data Science from an accredited University (Graduated or near completion) in 2022 and 2023.
• Previous experience up to one year will be considered.
• Software Development/ Programming skills – in any language (Java, Java Script, Python etc.)
• Knowledge (through university projects) in Database, data extraction and data manipulation using basic SQL.
• Technologist enthusiast with an interest in areas such as Data & Analytics, Cloud, DevOps, Digital, cyber security or another area of interest in technology
• Willingness to learn on the job and use your analytical and problem-solving skills.
• Strong attention to detail
• Strong communication skills
• A willingness to learn and should be flexible to explore different career options in the field of Business and IT

What we are offering:

TCS provides you with opportunities to join our global footprint within industries like banking and finance, communication and media, insurance, manufacturing, retail, travel and transport, utilities, energy and resources, telecommunications, hospitality and public services in Australia and New Zealand.

• An exceptional start in a global and multicultural environment with attractive market leading compensation
• Graduate program focused on constant innovation and application of emerging technology.
• Work with clients leading in their industries.
• Graduate induction, bespoke training and mentoring program
• Comprehensive opportunities for additional training and development through our Talent Development program and gamified online learning platform & apps
• A successful employee engagement & community platform
• Corporate Social Responsibility at the heart of what we do

  How to apply:

• Click on Gradconnection portal and apply with your latest resume and cover letter
• You can also send the resume and cover letter on mentioned email address. 
• You may indicate your technical strengths, interest in IT and projects you have worked on during your university degree 
• You may also mention your work right status and if you need help in work sponsorship. 

TCS Recruitment Process:

All shortlisted applicants will be undertaking various screenings and only selected graduates will be invited for final interviews. All successful hires will be inducted for full-time employment

• Job type: Graduate Jobs
• Disciplines: Computer Science
• Work rights: Australian Permanent Resident, Australian Working ... show more
• Locations: North Sydney, Sydney, ... show more

Jul 2024 (approx)

• Closing Date: 31st Aug 2024, 1:59 pm

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Electrical and Computer Engineering

College of engineering, ms in artificial intelligence engineering.

The Master of Science in Artificial Intelligence–Electrical and Computer Engineering is a three-semester (97-unit) program that offers students the opportunity to gain state-of-the-art artificial intelligence knowledge from an engineering perspective. Today, AI is driving significant innovation across products, services, and systems in every industry, and tomorrow’s AI engineers will have the advantage.

ECE students within the program will learn how to design and build AI-orchestrated systems capable of operating within engineering constraints. At Carnegie Mellon, we are leading this transformation by teaching students how to simultaneously design a system’s functionality and supporting AI mechanisms, including both its AI algorithms and the platform on which the AI runs, to produce systems that are more adaptable, resilient, and trustworthy.

Students pursuing the MS in AIE will be able to:

• Demonstrate knowledge of artificial intelligence methods, systems, tool chains, and cross-cutting issues, including security, privacy, and other ethical, societal, and policy challenges
• Apply ECE concepts and tools to enable AI systems and produce AI tools
• Be informed practitioners of AI methods to solve ECE and related problems, applying ECE domain knowledge whenever possible to enhance AI effectiveness
• Understand the limits of AI systems and apply these techniques within these limits
• Evaluate trade-offs involving technical capabilities and limitations, policy, and ethics in artificial intelligent systems

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Endless Opportunities

Whether pursuing academia or industry, this degree uniquely positions students for the future of research and high-demand careers with a mastery of integrating engineering domain knowledge into AI solutions.

For additional information about this college-wide initiative, please visit the College of Engineering's  MS in AI Engineering website .