phd in natural language processing

Joining the Group

The Stanford NLP Group is always on the lookout for budding new computational linguists. Stanford has a great program at the cutting edge of modern computational linguistics.

The best way to get a sense of what goes on in the NLP Group is to look at our research blog , publications , and students' and faculty's homepages . Our research centers around using probabilistic and other machine learning methods over rich linguistic representations in a variety of languages. The group is small, but productive and scientifically focused.

Prospective Graduate Students

Where do you apply for graduate (PhD or MS) study? Not directly to the NLP Group. Stanford graduate admissions are handled through individual departments, so you'll want to apply for admission through either the Linguistics Department or the Computer Science Department . Both departments have excellent graduate programs. Normally, you should apply to the one in which you have more background and greater interest in further study. Do make sure that you emphasize any research experience and results, and that you get letter writers who can speak convincingly about you. Decisions about admissions are made by the department's admissions committee. Because admissions committees represent the whole department and aim to select the best applicants regardless of specialization, you should direct your application towards an appropriately broad audience. And, as you probably know, Stanford admissions are quite competitive.

If you have questions about admissions, please check the graduate admissions web pages listed on the right, or write to the admissions email addresses listed. We NLP Group members attempt to answer specific NLP-related admissions questions (although sometimes we get too busy...), but in general it isn't necessary or helpful to contact us to let us know that you want to apply or have applied for admission.

Current Stanford Students

Are you a student at Stanford and interested in working on a project in NLP? Check out this page for details on how to apply to do research in the group.

Graduate Admissions Resources

Linguistics department, computer science department.

• Schools & departments

Centre for Doctoral Training in Designing Responsible Natural Language Processing PhD with Integrated Study

Awards: PhD with Integrated Study

Study modes: Part-time, Full-time

Funding opportunities

Placements/internships

Programme website: Centre for Doctoral Training in Designing Responsible Natural Language Processing

Introduction to Postgraduate Study

Join us online on 18 December at our live webinar session for an overview of postgraduate study and life at Edinburgh.

Find out more and register

Research profile

The Centre for Doctoral Training ( CDT ) in Designing Responsible Natural Language Processing ( NLP ) aims to develop doctoral graduates that represent a new paradigm of interdisciplinary NLP researcher; Individuals who can harness the full potential of NLP -based systems and create richer interactions between humans and AI . Our training will give students foundational knowledge across five fundamental skills domains, along with expertise in at least one of these areas. The training programme aims to create an NLP practitioner culture of responsibility, with graduates who are confident in combining technical expertise with:

consideration of users and use contexts

Students will train together in cohorts formed from various disciplines and background experiences. The students will be supported to collaborate on “team science” applied NLP projects. Through these projects, the students will also get the chance to work with some of our 70+ partners in the following sectors:

Programme structure

As part of the structure of our PhD with integrated studies, all students must study taught courses whilst completing the research elements of the traditional PhD programme. We have designed the programme to be flexible in the way credits are acquired. However, all students must successfully complete 180 taught credits over the first 3 years, plus the equivalent of 3 years of PhD research, spread over the 4-year programme. Out of the 180 credits, you will achieve 110 via mandatory courses that all CDT students take, and the remaining 70 credits from optional courses at the appropriate SCQF level.

Find out more about compulsory and optional courses

We link to the latest information available. Please note that this may be for a previous academic year and should be considered indicative.

Work placements/internships

Every student will have a placement, no more than 3 months long, during Years 2 or 3. The placements will involve students working in our partner’s teams, gaining hands-on industry experience and using skills developed through their training. We expect around two-thirds of placements to be with industry or in international research labs.

Training and support

Our students will gain the skills, knowledge and experience to study and design real-world applications of NLP in an interdisciplinary training environment, hosted by the Edinburgh Futures Institute ( EFI ) .

The training programme brings together world-leading researchers at our University to supervise students and guide them in their training and learning. Their expertise covers a range of subjects including:

informatics

linguistics

speech science

information science

digital humanities

As well as the formal credit-bearing courses all CDT students will be enrolled on, we have a variety of other training initiatives and activities within the CDT to:

enhance the learning opportunities for students

build links between students across different cohorts

personalise student’s training plans

Examples include:

entrepreneurship and innovation-oriented training

the Annual CDT Festival where students present their work

annual Partners' Summit

placements with partners

policy workshops and fellowships

responsible NLP speakers and masterclasses

support for student-led training

Students will be involved in the vibrant world-class and interdisciplinary research community at the EFI, with access to cutting-edge computational, design, fabrication and testing facilities across:

the School of Informatics

Edinburgh College of Art

This includes access to multiple state-of-the-art GPU clusters that enable work with large language models.

Career opportunities

We expect many students will seek diverse career pathways after their PhD such as in:

industrial research and development

entrepreneurship and social innovation

creating start-ups

Each cohort of students will participate in Fast-Track Impact training for PhD students in Year 1.

Students will also be able to participate in various events designed to foster both an intra- and an entrepreneurial mindset, delivered in collaboration with:

• Edinburgh Innovations
• the Bayes Centre

Additionally, the Bayes Centre and Edinburgh Innovations will provide students with access to University support to facilitate the commercialisation of their research. The support will include:

access to business advisors

accelerators

a network of investors and peers

[Updated 07 October 2024 to remove reference to the Bridge course]

Entry requirements

These entry requirements are for the 2025/26 academic year and requirements for future academic years may differ. Entry requirements for the 2026/27 academic year will be published on 1 Oct 2025.

A UK 2:1 honours degree, or its international equivalent, in an area related to the topic of the CDT, for example informatics, computer science, AI, cognitive science, mathematics, design, linguistics, psychology, philosophy, law, and social and political science.

International qualifications

Check whether your international qualifications meet our general entry requirements:

• Entry requirements by country
• English language requirements

Regardless of your nationality or country of residence, you must demonstrate a level of English language competency which will enable you to succeed in your studies.

English language tests

We accept the following English language qualifications at the grades specified:

• IELTS Academic: total 6.5 with at least 6.0 in each component. We do not accept IELTS One Skill Retake to meet our English language requirements.
• TOEFL-iBT (including Home Edition): total 92 with at least 20 in each component. We do not accept TOEFL MyBest Score to meet our English language requirements.
• C1 Advanced ( CAE ) / C2 Proficiency ( CPE ): total 176 with at least 169 in each component.
• Trinity ISE : ISE II with distinctions in all four components.
• PTE Academic: total 65 with at least 59 in each component. We do not accept PTE Academic Online.
• Oxford ELLT : 7 overall with at least 6 in each component.

Your English language qualification must be no more than three and a half years old from the start date of the programme you are applying to study, unless you are using IELTS , TOEFL, Trinity ISE or PTE , in which case it must be no more than two years old.

Degrees taught and assessed in English

We also accept an undergraduate or postgraduate degree that has been taught and assessed in English in a majority English speaking country, as defined by UK Visas and Immigration:

• UKVI list of majority English speaking countries

We also accept a degree that has been taught and assessed in English from a university on our list of approved universities in non-majority English speaking countries (non-MESC).

• Approved universities in non-MESC

If you are not a national of a majority English speaking country, then your degree must be no more than five years old at the beginning of your programme of study.

Find out more about our language requirements:

• Academic Technology Approval Scheme

If you are not an EU , EEA or Swiss national, you may need an Academic Technology Approval Scheme clearance certificate in order to study this programme.

Fees and costs

The CDT programme is fully funded and covers a stipend, tuition fees (both UK and overseas) and research and travel grant for 4 years, or 6 years for part-time study.

The funding does NOT cover visa fees and IHS for international students; these costs have to be covered by the student.

Scholarships and funding

By applying to the CDT programme you automatically apply for the full funding. There is no need to apply for any additional sources.

Search for scholarships and funding opportunities:

• Search for funding

Further information

• CDT Manager, Stefania Pasare
• Phone: +44 (0)131 651 7112
• Contact: [email protected]
• CDT Academic Director, John Vines
• Phone: +44 (0)131 650 9979
• CDT in Designing Responsible Natural Language Processing
• School of Informatics
• 10 Crichton Street
• Central Campus
• Programme: Centre for Doctoral Training in Designing Responsible Natural Language Processing
• School: Informatics
• College: Science & Engineering

Select your programme and preferred start date to begin your application.

PhD with Integrated Study in Designing Responsible Natural Language Processing - 6 Years (Part-time)

Phd with integrated study in designing responsible natural language processing - 4 years (full-time), application deadlines.

We strongly recommend you submit your completed application as early as possible, particularly if you are also applying for funding or will require a visa. We may consider late applications if we have places available.

• How to apply

You must submit two references with your application.

You must submit an application via the EUCLID application portal and provide the required information and documentation.

Your application needs to include your CV and a statement of intent and alignment with the CDT.

The programme website provides further application details:

• Designing Responsible Natural Language Processing

Find out more about the general application process for postgraduate programmes:

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Postdoctoral position in Natural Language Processing applied to Historical Research at the Faculty of Humanities, University of Copenhagen

The Saxo Institute, Faculty of Humanities, University of Copenhagen (UCPH), is pleased to announce an opening for a Postdoctoral Researcher in the field of Natural Language Processing ( NLP ) with a

Postdoctoral Research Fellow in Natural Language Processing

applied to core NLP tasks. The position presupposes a PhD degree or equivalent in Natural Language Processing, or in Computer Science with a clearly NLP -based thesis. The focus of the position is on

Research Assistant/Research Associate (Fixed Term)

Applications are invited for a Research Assistant / Research Associate post on the project EQUATE - a project that investigates how Natural Language Processing ( NLP ) could be made globally more

Internal Applicants Only - Research Associate

- Research Associate We are looking for a Research Associate to join the Cardiff NLP team in the School of Computer Science and Informatics at Cardiff University. In this role, you will: Be actively involved

Research Engineer II (Computer Science/Electrical Engineering)

A Corp Lab in NTU is looking for a Research Engineer to work on the NLP project. Key Responsibilities: Research and develop novel ML-based methodologies and algorithms for multilingual and

Lecturer in Computer Science (Advanced Machine Learning Methods for Natural Language Processing II)

meets 2-3 times per week. Timing is negotiable. Candidates with at least a Master's Degree and preferably a PhD in CL/ NLP or a closely related field, and teaching and/or industry experience in state

PhD Studentship: Leveraging Precision Medicine to Predict an Adverse Drug Reaction

to study the experiences of risk populations (patients with a lived experience of DAP) using semi-automated machine learning natural language processing ( NLP ) to code this qualitative data in

Research Fellow (Dept of Surgery)

for large-scale biological data analysis and integration Qualifications PhD in bioinformatics, statistics, computer science or related fields with good machine learning skills and software development skills

Post-Doctoral Fellow

intelligence to enhance medication management in the intensive care unit. By developing foundational technologies and conducting cutting-edge research in natural language processing ( NLP ) and machine learning

Assistant Professor in Linguistics and Multilingual Studies

to apply for two tenure-track positions in Linguistics and Multilingual Studies at the rank of Assistant Professor. Successful candidates must have a PhD at the time of appointment. The Linguistics and

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Department of Computer Science

• Department of Computer Science DIKU
• About the Department
• Open Positions
• PhD fellowship in Inte...

PhD fellowship in Interpretable Natural Language Processing

Department of Computer Science Faculty of SCIENCE University of Copenhagen

The Natural Language Processing Section at the Department of Computer Science, Faculty of Science at the University of Copenhagen invites applicants for a PhD fellowship in Interpretable Natural Language Processing.

Start date is (expected to be) 1st September 2025 or as soon as possible thereafter.

The position The PhD fellowship is offered with   Pepa Atanasova   as the primary (de facto) supervisor, and co-supervised with   Isabelle Augenstein , who serves as the formally designated principal supervisor. The successful candidate will engage in developing innovative methods for interpreting and explaining the inner workings of natural language processing models. The research will broadly align with the   main interests of primary supervisor   and the objectives of the   CopeNLU group . It may include exploring the mechanisms by which language models process and represent knowledge, devising methods to provide reliable explanations for models' decision-making processes, or developing techniques to ensure accountability in model’s behavior.

While the overall focus of the PhD will be within the area of NLP interpretability and explainability, the specific research direction will be tailored in collaboration with the candidate to align with their interests and the group's research goals. The candidate will join a vibrant research team that includes collaborators from CopeNLU and other international partners, fostering a dynamic and interdisciplinary environment conducive to impactful research.

Who are we looking for? Applicants should hold a MSc degree or equivalent in Computer Science or a related field, and have good written and oral English skills. The assessment of your qualifications will also be made based on previous scientific publications (if any) and relevant work experience. The ideal candidate would have an education background, prior research or work experience in ML or NLP.

Our group and research- and what do we offer? The successful candidate will join the  CopeNLU group  at the University of Copenhagen. CopeNLU is a vibrant and collaborative research group led by Isabelle Augenstein and Pepa Atanasova with a focus on researching methods for tasks that require a deep understanding of language, as opposed to shallow processing. We are interested in core methodology research on, among others, learning with limited training data, interpretable and explainable AI; as well as applications thereof to tasks such as fact checking, gender bias detection and question answering. With a strong focus on both foundational and applied research, we provide a platform for exploring cutting-edge topics in NLP, while also emphasizing the importance of transparent and responsible AI development.

We are affiliated with the  Natural Language Processing Section  in the Department of Computer Science, Faculty of SCIENCE, University of Copenhagen, as well as with the  Pioneer Centre for AI , at the Department of Computer Science, University of Copenhagen. The group is currently co-located with the Pioneer Centre for AI in central Copenhagen. The Natural Language Processing Section provides a strong, international and diverse environment for research within core as well as emerging topics in natural language processing. The Natural Language Processing research environment at the University of Copenhagen is internationally leading, as e.g. evidenced by it being ranked top-5 in Europe according to CSRankings. Further information about research at the Department is available here:  https://di.ku.dk/english/research/  .

Principal supervisor  is  Prof. Isabelle Augenstein, Department of Computer Science, email:  [email protected]  The PhD student will be co-supervised by Pepa Atanasova, email:  [email protected]  .

The PhD programme You can undertake the PhD programme as:

A  three year full-time study  within the framework of  the regular PhD programme  ( 5+3 scheme) ,  if you already   have an education   equivalent to a relevant Danish master’s degree.

Getting into a position on the regular PhD programme

Qualifications needed for the regular programme To be eligible for the regular PhD programme, you must have completed a degree programme, equivalent to a Danish master’s degree (180 ECTS/3 FTE BSc + 120 ECTS/2 FTE MSc) related to the subject area of the position, i.e. NLP and ML. For information of eligibility of completed programmes, see   General assessments for specific countries   and   Assessment database .

Terms of employment in the regular programme Employment as PhD fellow is full time and for maximum 3 years.

Employment is conditional upon your successful enrolment as a PhD student at the PhD School at the Faculty of SCIENCE, University of Copenhagen. This requires submission and acceptance of an application for the specific position formulated by the applicant.

Terms of appointment and payment accord to the agreement between the Danish Ministry of Taxation and The Danish Confederation of Professional Associations on Academics in the State. The position is covered by the Protocol on Job Structure.

Responsibilities   and tasks in the PhD programme

• Carry through an independent research project under supervision
• Complete PhD courses corresponding to approx. 30 ECTS / ½ FTE
• Participate in active research environments, including a stay at another research institution, preferably abroad
• Teaching and knowledge dissemination activities
• Write scientific papers aimed at high-impact journals
• Write and defend a PhD thesis on the basis of your project

We are looking for the following qualifications:

• Professional qualifications relevant to the PhD position
• Relevant publications
• Relevant work experience
• Other relevant professional activities
• Curious mind-set with a strong interest in Interpretable Natural Language Processing
• Good language skills

Application and Assessment Procedure Your application including all attachments must be in English and submitted electronically by clicking APPLY NOW below.

Please include : 

• Cover Letter detailing your motivation and background for applying for this PhD position.
• Research Statement   detailing your desired research focus and goals for the PhD studies within the scope of the specified position.
• Curriculum vitae including information about your education, experience, language skills and other skills relevant for the position;
• Original diplomas for Bachelor of Science or Master of Science and transcript of records in the original language, including an authorized English translation if issued in another language than English or Danish. If not completed, a certified/signed copy of a recent transcript of records or a written statement from the institution or supervisor is accepted.
• Publication list (if possible);
• Reference letters (if available);

Application deadline:

The deadline for applications is  15th January 2025 , 23:59 CET.

We reserve the right not to consider material received after the deadline, and not to consider applications that do not live up to the abovementioned requirements.

The further process After deadline, a number of applicants will be selected for academic assessment by an unbiased expert assessor. You are notified, whether you will be passed for assessment.

The assessor will assess the qualifications and experience of the shortlisted applicants   with respect to the above mentioned research area, techniques, skills and other requirements. The assessor will conclude whether each applicant is qualified and, if so, for which of the two models.  The assessed applicants will have the opportunity to comment on their assessment. You can read about the recruitment process at   https://employment.ku.dk/faculty/recruitment-process/ .

Interviews with selected candidates are expected to be held between 3rd -15th February 2025.

Questions For specific information about the PhD fellowship, please contact   [email protected]   .

General information about PhD study at the Faculty of SCIENCE is available at the PhD School’s website:   https://www.science.ku.dk/phd/ .

The University of Copenhagen wishes to reflect the surrounding community and invites all regardless of personal background to apply for the position. 

SØG STILLINGEN

Københavns Universitet giver sine knap 10.000 medarbejdere muligheder for at udnytte deres talent fuldt ud i et ambitiøst, uformelt miljø. Vi sikrer traditionsrige og moderne rammer om uddannelser og fri forskning på højt internationalt niveau. Vi søger svar og løsninger på fælles problemer og gør ny viden tilgængelig og nyttig for andre.

Time: 15 Jan. 2025

Place: Department of Computer Science

• School of Computer Science
• Research Groups

Natural Language Processing

The Natural Language Processing Research Group, established in 1993, is one of the largest and most successful language processing groups in the UK and has a strong global reputation.

Natural Language Processing (NLP) is an interdisciplinary field that uses computational methods:

To investigate the properties of written human language and to model the cognitive mechanisms underlying the understanding and production of written language (scientific focus)

To develop novel practical applications involving the intelligent processing of written human language by computer (engineering focus) 

Research Themes

Building applications to improve access to information in massive text collections, such as the web, newswires and the scientific literature

Providing resources - both data and processing resources - for research and development in NLP. Includes platforms for developing and deploying real world language processing applications, most notably GATE, the General Architecture for Text Engineering.

 Building applications to translate automatically between human languages, allowing access to the vast amount of information written in foreign languages and easier communication between speakers of different languages.

Investigating techniques for determining when texts or portions of texts have been reused or where portions of text do not fit with surrounding text. These techniques have applications in areas such as plagiarism and authorship detection and in discovery of hidden content.

Developing applications with human-like capabilities for processing language requires progress in foundational topics in language processing. Areas of interest include: word sense disambiguation, semantics of time and events.

Social Media, Online Disinformation, and Elections: A Quantitative, "Big Data" Perspective. 

GATE in Biomedical Text Processing

Core members

Academic staff.

• Prof . Nikolaos Aletras  (Head of Group)
• Prof. Kalina Bontcheva
• Prof. Hamish Cunningham
• Prof. Rob Gaizauskas  
• Dr Mark Hepple
• Dr Chenghua Lin
• Dr Nafise Sadat Moosavi
• Dr Carolina Scarton
• Dr Xingyi Song
• Dr Mark Stevenson
• Prof. Aline Villavicencio
• Dr  Xi Wang
• Dr Cass Zhixue Zhao

Senior research staff

• Dr Diana Maynard  (Deputy Head of Group)
• Ibrahim Abu Farha
• Mehmet Bakir
• Dr Emma Barker
• Dr Mark Greenwood
• Dr Fatima Haouari
• Freddy Heppell
• Tashin Khan
• Mugdha Pandya
• Olesya Razuvayevskaya
• Ian Roberts
• Iknoor Singh
• Xingwei Tan
• Jake Vasilakes
• Ahmad Zareie
• Jonathan Foster
• Prof. Jochen Leidner

Publications

Here you can find research publications for the  Natural Language Processing Research Group , listed by academic.  The head link navigates to the official web page for the relevant academic (with highlighted favourite publications).  The remaining links navigate to their DBLP author page, their Google Scholar citations page and optionally a self-maintained publications page.

Related information

Interested in doing a PhD? Find out more

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The University's cross-faculty research centres harness our interdisciplinary expertise to solve the world's most pressing challenges.

King's College London

Natural language processing.

The Natural Language Processing (NLP) Group at KCL is comprised of PhD and postdoctoral students, professors and others who are interested in solving computational problems related to the understanding of human language. This encompasses a wide range of topics including sentiment analysis, topic/event extraction, question answering, cross-modal retrieval, text illustration, social media analysis and many more, typically approached with machine learning.

All images have been generated using DALL-E.

Related departments

• Department of Informatics
• Faculty of Natural, Mathematical & Engineering Sciences