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PhD Study at MMLL

Which of the faculty's sections offer phd study.

PhD study is offered in each of the Faculty's Sections: French , German , Italian , Slavonic Studies , Spanish & Portuguese ,  Theoretical and Applied Linguistics , and also in the Centre for Film and Screen Studies .

Overview of a PhD course

A PhD (formally known as Doctor of Philosophy) is a substantial piece of original scholarship, for which the research and writing-up can be reasonably expected to be completed in three to four years (or for part-time students, where this is offered, five to seven years).  In MMLL the maximum word limit is 80,000 words. For the purposes of a PhD, the notion of originality means that the thesis should represent a significant contribution to learning, through the discovery of new knowledge, or through the connection of previously unrelated facts, or the development of new theory, or the revision of older views, or some combination of these different criteria. 

During the period of research, students will  work closely with a Supervisor who is a specialist in their research area. Students are additionally assigned an Advisor who acts as a second point of contact for academic advice. In addition to providing specialist supervision, the Faculty runs a programme of professional training for the benefit of all research students.

Requirements

Please see the central prospectus for the exact requirements (you will need to search for the particular PhD course you are interested in).​  It is noted that language skills in a particular area may   be required depending on the specific nature of your research proposal.

How to Apply & Funding

You can apply online at the Postgraduate Admissions website.  Their site also provides detail on the course structure and content, fee rates, information on the College system, and information regarding the application process. 

Please find further information regarding applications and funding on our Applying and funding page and our Applying: PhD page .

Supporting Documents

When you apply online you will be asked to upload your supporting documents:

• Academic transcripts for any degree-level courses you have taken.
• Evidence of your English ability (if you are not a native English speaker).
• A sample of writing, of approx 5,000-10,000 words. The sample can be either an essay produced during master's-level studies or a section of a dissertation, and must be a single-authored work. 
• A research proposal, approx 500-1,000 words, written in English.
• Your curriculum vitae (CV ​ ).

In the applications portal you will be asked to enter details of your nominated referees. They will then be sent an automated email asking them to provide an electronic reference via the applications portal. It is recommended that you allow several weeks before the application/funding deadline to allow time for this process.

Further information on supporting documents can be found on the Postgraduate Admissions website.

Finding a Prospective Supervisor

Doctoral study is a team effort. It is conducted under the supervision of at least one member of Cambridge’s academic staff. Before submitting a PhD application to Cambridge, students are strongly recommended to approach relevant professors and enquire about the possibility of their service as a Supervisor. This approach is normally done via email, and it is completely informal. Its purpose is help you determine the availability and degree of research fit of relevant professors at Cambridge. As a first step, explore the Faculty's Sections and Centres (see Which Sections? above and then follow the relevant link to staff pages) and familiarise yourself with the publications and projects undertaken by our professors. Once you have identified a potential supervisor, please send an expression of interest to them via email with your CV and as much of your research proposal as possible. Please do not reach out to more than one professor at the same time. Making such an approach will help you nominate a Supervisor when you eventually submit your application. The Faculty will take this nomination into account, although there is no guarantee that this Supervisor will be formally appointed if you are accepted to the PhD. The MMLL Degree Committee regularly monitors the supervision load for each member of academic staff and may decide to appoint another suitable Supervisor, if necessary. Please note that admission to the PhD is made by committee at the Faculty level in accordance with University standards and guidelines; potential Supervisors can only contribute to admission decisions.

Consideration of Applications

Applicants who apply for US Gates funding by the October funding deadline may normally expect to receive an admissions decision in December.  All other applicants who apply by the funding deadline in January may normally expect to receive a decision before the end of March, and the majority of offers are made in February and March.  Following the funding deadlines, applications are processed on a rolling basis and applicants may normally expect a decision within 12 weeks following the submission of their completed application and required supporting documents.  Occasionally, applicants may not receive a decision within the normal timeframe due to being placed on a reserve list.  If this is the case then the Faculty will be in touch to let applicants know.  Normally the latest date for decisions to be communicated is the end of June.

Consortium in Latin American Cultural Studies 

If you are applying to the Section of Spanish and Portuguese and wish to work on any topic within Latin American literary, visual, or cultural studies, you may wish to read about the  Consortium in Latin American Cultural Studies for PhD students.

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PhD in Physics

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PhD in Physics (3+ years)

The majority of postgraduate students (about 110 are accepted each year) carry out research at the Cavendish Laboratory towards a PhD degree.

For admission to the PhD, the Postgraduate Admissions Office normally requires applicants to have achieved the equivalent of a UK Masters (Pass) . Applicants should obtain the equivalent of:

• at least a 2:i in a UK four-year "undergraduate Master's" (Honours) degree,  OR
• at least a 2:i in a UK three-year Bachelor's (Honours) degree plus a relevant one/two -year UK Master's degree.

All applicants are assessed individually on the basis of their academic records.

Full-time students must spend at least three terms of residence in Cambridge and nine terms of research. If you are undertaking a placement or internship away from Cambridge for more than two weeks you need to apply for leave to work away.

Final examination involves the submission of a thesis of not more than 60,000 words followed by an oral examination (or viva) of the thesis and the general field of physics into which it falls.

Successful applicants are assigned to a research supervisor, a specialist in part or all of the student's chosen research field, and joins a research group which might vary in size between 4 and 80 individuals. Although the supervisor is responsible for the progress of a student's research programme, the extent to which a postgraduate student is assisted by the supervisor or by other members of the group depends almost entirely on the structure and character of the group concerned. The research field is normally determined at entry, after consideration of the student's interests and facilities available.

A list of current research projects is published and available on the  research pages  of our website, and more detailed information about specific research areas can be obtained from the relevant academic staff. The student, however, may work within a given field for a period of time before his or her personal topic is determined.

There is no requirement by the University of attendance at formal courses of lectures for the PhD. Postgraduate work is largely a matter of independent research and successful postgraduates require a high degree of self-motivation. Nevertheless, lectures and classes may be arranged, and students are expected to attend both seminars (delivered regularly by members of the University and by visiting scholars and industrialists) and external conferences. In addition, postgraduate students carry out first- and second-year physics undergraduate supervision and assist with practical work and theoretical examples classes in the Department.

Lectures within all the faculties of the University are open to any member of the University, and a physics postgraduate student has the opportunity of attending lectures not only within the undergraduate Physics and Theoretical Physics course, but also in any other subject area or faculty.

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PhD in Economics

• Advanced Diploma in Economics
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This is the most advanced programme of graduate studies in Economics at Cambridge. Upon its completion, candidates are awarded a PhD degree for producing a thesis of high-quality, original, and publishable research over a period of four years (full-time) and seven years (part-time).

A good number of our PhD students receive full or partial funding for their studies, from a variety of funding bodies, such as the ESRC and the Gates Foundation .

Our PhD students receive high quality training on a variety of research methods and are exposed to cutting edge research conducted by our own Faculty members, as well visitors to the Faculty (via the Cambridge-INET Institute , seminars, PhD workshops, locally organised conferences, etc.). Faculty members can supervise a wide range of topics from six broadly defined research areas: microeconomic theory, macroeconomics, econometrics, applied microeconomics, economic history and alternative approaches to economics.

PhD students in Cambridge benefit from a high faculty-to-student ratio and therefore form close relationships with many Faculty members. They also forge strong links with our post-doctoral researchers, and they actively participate in the Faculty’s vibrant research life. They have access to a wide range of facilities, such as their own desk/office space in the same building as regular Faculty members, computing equipment, a variety of software and access to a wide range of databases.

PhD students are encouraged to attend academic conferences and showcase their research work in a variety of ways. Upon completions of their studies, many of our PhD students become academics, or researchers at international or government research institutions (see recent job market placements here ).

Explore here the profiles of our current PhD students.

To obtain the degree of PhD in Economics, students need to:

1. Obtain the Certificate of Postgraduate Study (CPGS) . If accepted for the PhD degree, you will be registered initially for the Certificate of Postgraduate Study (CPGS) in Economics. Students registered for the CPGS are required to:

• Attend the 'How to do Economics' lecture course. Other postgraduate courses in research methods are organised by the Schools of Humanities and Social Sciences and the Physical Sciences, and are available to all PhD students.  
• Undertake a minimum of four courses from PhD or MPhil Modules from at least two subject areas. You must achieve a pass mark (60%) on each component of the coursework. Students who fail any examinations will be called for a viva on the coursework.

• Write a research proposal (maximum length 10,000 words) that should include a review of the relevant literature, a research question, and outline of a research design and methods. The expectation is that this proposal will be for a piece of research that could form the basis of one chapter of a PhD dissertation. You will be given an oral examination on this piece of work and must perform to a satisfactory standard.  
• Attend (a) one of the three research workshops (on microeconomics, macroeconomics or econometrics) at which research students present both their own work and recent papers in the literature - assessment of workshops will be arranged by course organisers; (b) attend at least one of the Faculty's general seminars in which papers are given both by outside speakers and Faculty members;  
• To be registered for the PhD submit an acceptable piece of research (first year chapter) of not more than 20,000 words. The piece of research submitted must be of a standard that would enable it to form the basis of one-third of your eventual PhD thesis. This means that it must contain research that could be expanded upon to constitute one-third of the PhD thesis.

2. Once upgraded to PhD status, a student concentrates on her or his PhD dissertation. In general the thesis format is either in the form of a book divided into chapters, or of three or more connected articles; in either case, the Faculty has a strict limit of 60,000 words. As research progresses, there will be opportunities to present work in progress at research workshops attended by Faculty members and research students. PhD students will also be required to attend research seminars given by outside speakers and Faculty members. 

Upon completion and submission of the PhD thesis, students do an oral examination (viva) with two examiners, one internal to the University of Cambridge (not the supervisor or research advisor), and one external (from any other University in the UK or the rest of the world).

After a successful thesis defence, the examiners recommend awarding the degree of PhD.

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Application process for PhD and EdD

You are required to identify a potential supervisor before submitting your PhD/EdD application. When you contact potential supervisors, you should discuss their availability to supervise and the fit between your proposed PhD project and the area of their research. Indication in principle that the supervisor is willing to supervise your project does not guarantee an offer of admission. This is because potential supervisors cannot independently make a final decision on admission to the PhD/EdD. Potential supervisors will only indicate if, pending a successful application, they would in principle be able to supervise you. This is because the fit between your doctoral research proposal (see below) and the specific research field of the potential supervisor is an essential component of doctoral studies.

Time and interest permitting, the potential supervisor may advise on how a research proposal might be developed or improved. Such advice does not guarantee an offer of admission.

► You can find academic staff profiles, including supervision availability, in the research section on the Faculty website.  ► A list of potential supervisors for the 2024 admission cycle is available here .

Further information about how and when to apply for the PhD/EdD  is available from the Postgraduate Admissions Office.

Progression from Masters to the Doctoral programme

If you are a student on the Faculty Masters programme and you intend to proceed straight onto the doctoral programme, please note that continuation is not automatic and must be preceded by an application to the doctoral programme, regardless of funding arrangements, as well as meeting the academic requirements for continuation.

Supervisors

All applicants are required to name a potential supervisor on your application because they will be the first person to review your application after you submit it. This is the potential supervisor whom you would have contacted ahead of submitting your application.

If the potential supervisor would like to take the application further, you may be contacted for an interview.

If the potential supervisor is not available, your application will be reviewed by the doctoral admissions team to determine whether another supervisor may be identified.

Given the range of areas of research and fields of expertise represented in the Faculty, not identifying a supervisor at the point of application is unlikely to result in a match being identified through this route.

Applicants are strongly encouraged therefore to contact supervisors ahead of submitting their application. If you have not identified a supervisor at the point of application, we may not be able to identify any supervisor with aligned research interests and therefore we may not be able to make an offer of admission.

Admissions decisions

Upon submission of the application, the named potential supervisor reviews the full application and makes a recommendation to the Faculty of Education doctoral admissions team. The doctoral admissions team further reviews the full application and makes a final decision as to whether an offer of admission will be made, and what conditions for admission may apply.

Please note that this final decision normally takes up to 12 weeks to reach the applicant, but may on occasion take longer.

Applicants who have applied for funding, applied by the appropriate funding deadline, and have an offer of admission (even if this has not yet been communicated to the applicant) will be considered for funding. 

Consideration for funding starts with a ranking of all eligible applications, undertaken by a panel convened by the Faculty of Education doctoral admissions team. This panel include academics working in a range of fields and research areas and applying a large variety of methods in their own work. The panel generates a full set of funding recommendations on behalf of the Faculty. 

Funding recommendations are then forwarded from the Faculty of Education to the University's central Postgraduate Funding Committee, who review all applications across the University and make recommendations for funding allocations. Decisions about funding for doctoral places are communicated to applicants starting in February, and can be announced as late as the summer before entry.

Unfortunately, there is limited funding and we cannot therefore promise to fund every applicant who receives an offer of a place. You may receive an offer to study on our doctoral programme, without receiving any funding.

The Faculty of Education doctoral admissions team, the Cambridge Trust, the ESRC DTP and the AHRC DTP are all committed to supporting scholars from diverse backgrounds to join our doctoral programmes. When it comes to funding, we consider applications holistically, weighing up the research proposal, prior academic record, references, and evidence of resilience and other relevant personal circumstances.

The Research Proposal

All doctoral applicants are required to submit a research proposal of up to 1,500 words (exclusive of bibliography/reference list) outlining their proposed research project.

Please read Guidance for research proposal

Important note

It is very important that the area you want to work in is broadly compatible with our research interests and that you name a potential supervisor on your application

The Personal Statement

All doctoral applicants are required to submit a personal statement of up tp 1,500 words providing a holistic account of their reasons for applying and their educational and professional experiences that have led them to this point.

Contextual information you provide in the personal statement allows the admissions team to make recommendations for funding in the most equitable way possible, based on the information we receive from applicants.

Please read Guidance for personal statement .

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Supervision

Candidates work closely with their supervisor who is assigned to them after a candidate has been accepted and before the commencement of their studies. The supervisor will be a specialist in the general field in which you propose to work, although they may not be an expert on your particular topic of research. Your supervisor will assist you in refining your research topic, oversee the general direction of your work, and ensure that what you are doing is up to the standard expected for the degree towards which you are working. You can expect to meet your supervisor on average once a month to report on your progress, and more frequently than this if necessary. How much you write in a given period will vary, but as a rule of thumb you will usually be expected to produce at least one substantial piece of written work each term.

Prospective PhD students should research the Faculty thoroughly before applying to ensure that there is a Faculty member with appropriate expertise to oversee the proposed project. The Faculty’s research map might be of use as a starting point here, as will the Faculty academic staff profiles .

In addition to their supervisor, PhD students are assigned an advisor, who is a member of the Faculty with expertise in the student’s field. The student has a formal advisory meeting with the supervisor and the advisor once a year. The advisor is also available for less formal consultation from the outset.

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PhD in Sociology

The PhD in Sociology offers a world-class programme of research study in sociology supervised by experts in their respective fields. The Department of Sociology at the University of Cambridge is ranked first for Sociology in the  Guardian's Best Universities league table  and first for Sociology in the  Complete University Guide League Table 2024 . And the  QS World University rankings  list our departments as 2nd out of over 500 Sociology Departments across the world in 2023.

In the first year you are encouraged to take research methods courses offered by the Department and the  Social Science Research Methods Programme (SSRMP)  to build the methodological grounding of your individual research projects. 

The Department also offers a programme of seminars covering transferable skills such as academic writing, presentation skills and in-depth information about how to progress the PhD and the academic career. PhD students are supported by their supervisor and a faculty adviser.

Watch our open day video

The Programme

The course aims to provide all students with the skills they need to be professional researchers and academics. There is an organised programme of courses for first-year PhD students, which has three major components:

• Basic academic and research skills, designed to provide the essential tools of academic work
• The core training programme, which covers issues of social science research in general
• Issues of research specific to particular disciplines or areas of interest, and research design, including the integration of methodological, theoretical and substantive issues

The standard period for PhDs is 3-4 years full-time or 5-7 years part-time.    Click here for further information about part-time PhD studies .

Meet our Candidates

What you can do with your phd.

Students who complete graduate programmes in Sociology have the opportunity to develop the analytical and writing skills to help them succeed in academia but also in careers such as health and social care, marketing and public relations, politics, and education, amongst others.

Postgraduate Prospectus

The PG prospectus details all the courses on offer at Cambridge, as well as introducing the different Colleges and describing the admissions process.

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Cambridge centre for data-driven discovery, currently advertised phd studentships.

• The majority of current PhD studentships are listed on the  University's Jobs site
• For a full list of departments and faculties at the University, visit this page where you can learn more about the research interests within each department
• To find academics you might like to work with, use our directory

Graduate Admissions

The  Graduate Admissions  office provides a range of information on postgraduate programmes at Cambridge, along with a step-by-step guide to the application process. It is advisable to start researching funding opportunities at least a year before your course begins.

MPhil and PhD course relevant to data science - from across University of Cambridge

Please visit the relevant pages and contact the relevant education provider if you have queries. You should pay particular attention to the entry requirements and guidance for applicants there.

MPhil in Machine Learning and Machine Intelligence - an eleven month full-time programme offered by the Machine Learning Group, the Speech Group, and the Computer Vision and Robotics Group in the Cambridge University Department of Engineering.  The course aims to teach the state-of-the-art in machine learning, speech and language processing, and computer vision; to give students the skills and expertise necessary to take leading roles in industry and to equip them with the research skills necessary for doctoral study at Cambridge and other universities.

PhD programme in Advanced Machine Learning - The Machine Learning Group is based in the Department of Engineering, and encourages applications from outstanding candidates with academic backgrounds in Mathematics, Physics, Computer Science, Engineering and related fields, and a keen interest in doing basic research in machine learning and its scientific applications. 

Cambridge Centre for AI in Medicine - Cambridge Centre for AI in Medicine (CCAIM) is a multi-disciplinary centre established by the University of Cambridge in 2020 to develop pioneering AI machine learning (ML) technologies that will transform biomedical science, medicine and healthcare. PhD studentships are oten available, please check their website for details.

SynTech Centre for Doctoral Training - EPSRC Centre for Doctoral Training in Next Generation Synthetic Chemistry Enabled by Digital Molecular Technologies. An interdisciplinary cohort-driven programme to produce the next generation of molecule making scientists by combining Synthetic Chemistry, Chemical Engineering, Engineering, Machine Learning and Artificial Intelligence.

Advanced Computer Science MPhil  - The MPhil in Advanced Computer Science (the ACS) is designed to prepare students for doctoral research, whether at Cambridge or elsewhere. Typical applicants will have undertaken a first degree in computer science or an equivalent subject, and will be expected to be familiar with basic concepts and practices. The ACS is a nine–month course which starts in early October and finishes on 30 June. It covers advanced material in both theoretical and practical areas as well as instilling the elements of research practice.

Application of Artificial Intelligence to the study of Environmental Risks MRes and PhD - The UKRI Centre for Doctoral Training in the Application of Artificial Intelligence to the study of Environmental Risks (AI4ER) trains researchers (through several multidisciplinary cohorts) to be uniquely equipped to develop and apply leading-edge computational approaches to address critical global environmental challenges by exploiting vast, diverse and often currently untapped environmental data sets. Embedded in the outstanding research environments of the University of Cambridge and the British Antarctic Survey (BAS), the AI4ER CDT addresses problems that are relevant to  building resilience to environmental hazards and managing environmental change .

Postgraduate Study in Mathematics - Various postgraduate courses of a mathematical nature are available at the University of Cambridge, including both taught courses and research degrees.

Mathematics of Information PhD  - This cutting-edge training Centre in the Mathematics of Information produces a new generation of leaders in the theory and practice of modern data science, with an emphasis on the mathematical underpinnings of this new scientific field. The Cambridge Mathematics of Information (CMI) PhD is a four-year course leading to a single PhD thesis.

Cambridge Computational Biology Institute MPhil and PhD ​ - The MPhil in Computational Biology course is aimed at introducing students in the biological, mathematical and physical sciences to quantitative aspects of modern biology and medicine, including bioinformatics. The course has been developed by the Cambridge Computational Biology Institute and is run by the Department of Applied Mathematics and Theoretical Physics at the Centre for Mathematical Sciences (CMS).

Centre for Scientific Computing MPhil and PhD  - The MPhil programme on Scientific Computing is offered by the University of Cambridge as a full-time course which aims to provide education of the highest quality at Master’s level. A common route for admission into our PhD programme is via the Centre’s MPhil programme in Scientific Computing.

Part III Mathematics  - Part III is a 9 month taught masters course in mathematics.  It is an excellent preparation for mathematical research and it is also a valuable course in mathematics and in its applications for those who want further training before taking posts in industry, teaching, or research establishments. Students admitted from outside Cambridge to Part III study towards the Master of Advanced Study (MASt).  Students continuing from the Cambridge Tripos for a fourth year, study towards the Master of Mathematics (MMath).  The requirements and course structure for Part III are the same for all students irrespective of whether they are studying for the MASt or MMath degree. There are over 200 Part III (MASt and MMath) students each year; almost all are in their fourth or fifth year of university studies. 

School of Clinical Medicine Graduate Training Office - Prospective students interested in pursuing a graduate degree course in a subject area related to clinical medicine at the University of Cambridge should consult the School’s individual departmental websites for detailed information about the courses which they run and the University’s Graduate Admissions website for information on the application process and on funding opportunities.

Centre for Doctoral Training in Data, Risk And Environmental Analytical Methods  - The CDT embraces a wide range of world-leading Doctoral research in the area of Big Data and Environmental Risk Mitigation. The CDT research underway seeks to utilise emerging technologies, techniques and tools, to more accurately monitor the environment, enabling cutting edge research. To provide end-users with more integrated information at improved temporal and spatial resolutions to deliver solutions to environmental challenges (both acute and long- term). Funded by  NERC  (the Natural Environment Research Council, NERC Ref: NE/M009009/1), the DREAM (Data, Risk and Environmental Analytical Methods) consortium is made up of Cranfield, Newcastle, Cambridge and Birmingham universities.

Centre for Doctoral Training in Data Intensive Science  - The Cambridge CDT in Data Intensive Science is an innovative, interdisciplinary centre, distributed between the Department of Physics (Cavendish Laboratory), Department of Applied Mathematics and Theoretical Physics (DAMTP), Department of Pure Mathematics and Mathematical Statistics (DPMMS) and the Institute of Astronomy (IoA).

MPhil in Data Intensive Science - This course aims to take science graduates and to prepare them for data intensive research careers by providing advanced training in three key areas – Statistical Analysis, Machine Learning, and Research Computing – and their application to current research frontiers.

Cambridge Digital Humanities - The MPhil provides the opportunity to specialise in a chosen subject area as well as an advanced level introduction to DH approaches, methods and theory. The course provides critical and practical literacy, the chance to advance an extant specialization by re-contextualizing it in relation to advanced theoretical work, and the chance to develop as a DH scholar.

The Cambridge Centre for Data-Driven Discovery (C2D3) brings together researchers and expertise from across the academic departments and industry to drive research into the analysis, understanding and use of data science and AI. C2D3 is an Interdisciplinary Research Centre at the University of Cambridge.

• Supports and connects the growing data science and AI research community 
• Builds research capacity in data science and AI to tackle complex issues 
• Drives new research challenges through collaborative research projects 
• Promotes and provides opportunities for knowledge transfer 
• Identifies and provides training courses for students, academics, industry and the third sector 
• Serves as a gateway for external organisations 

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The PhD programme

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The PhD is awarded after three to four years of full-time research (or five to seven years of part-time study) on the basis of a dissertation of 80,000 words (exclusive of footnotes, appendices and bibliography, but subject to an overall word limit of 100,000 words exclusive of bibliography, table of contents and any other preliminary matter). Examination for the PhD involves an oral examination (viva) by two examiners.

Research students who intend to undertake PhD research are in the first instance automatically registered for a one-year research training programme leading to the Certificate of Postgraduate Study (CPGS) in Legal Studies. They are assigned a supervisory team by the Degree Committee of the Faculty, ordinarily consisting of a supervisor (who is principally responsible for directing and assisting the research) and an advisor (who provides a second point of contact for academic advice). At the end of the first year, the Degree Committee decides whether students should be registered for the PhD. This decision is taken on the basis of the student’s personal progress log, first-year dissertation of 15,000 words, viva conducted by two assessors from within the Faculty, and outline of plans for the full research project. Candidates who successfully complete the requirements of the CPGS and the first-year progress review are retrospectively registered for the PhD.

All full-time PhD students are ordinarily required to be resident in Cambridge for the duration of their research (save where given leave to work away from Cambridge for academic reasons or whilst undertaking fieldwork), and during the first year in particular must attend weekly research training sessions in the Faculty.

This overview of the PhD programme must be read in conjunction with the detailed information available under the 'Courses' section (see, in particular, the Course Directory) of the Postgraduate Admissions website . Further information on postgraduate admission to research courses in the Faculty of Law is available from [email protected] or +44 (0)1223 330039.

The Faculty of Law The David Williams Building 10 West Road Cambridge CB3 9DZ United Kingdom

Telephone: +44 1223 330033 Email: [email protected]

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PhD Programme in Advanced Machine Learning

The Cambridge Machine Learning Group (MLG) runs a PhD programme in Advanced Machine Learning. The supervisors are Jose Miguel Hernandez-Lobato , Carl Rasmussen , Richard E. Turner , Adrian Weller , Hong Ge and David Krueger . Zoubin Ghahramani is currently on academic leave and not accepting new students at this time.

We encourage applications from outstanding candidates with academic backgrounds in Mathematics, Physics, Computer Science, Engineering and related fields, and a keen interest in doing basic research in machine learning and its scientific applications. There are no additional restrictions on the topic of the PhD, but for further information on our current research areas, please consult our webpages at http://mlg.eng.cam.ac.uk .

The typical duration of the PhD will be four years.

Applicants must formally apply through the Applicant Portal at the University of Cambridge by the deadline, indicating “PhD in Engineering” as the course (supervisor Hernandez-Lobato, Rasmussen, Turner, Weller, Ge and/or Krueger). Applicants who want to apply for University funding need to reply ‘Yes’ to the question ‘Apply for Cambridge Scholarships’. See http://www.admin.cam.ac.uk/students/gradadmissions/prospec/apply/deadlines.html for details. Note that applications will not be complete until all the required material has been uploaded (including reference letters), and we will not be able to see any applications until that happens.

Gates funding applicants (US or other overseas) need to fill out the dedicated Gates Cambridge Scholarships section later on the form which is sent on to the administrators of Gates funding.

Deadline for PhD Application: noon 5 December, 2023

Applications from outstanding individuals may be considered after this time, but applying later may adversely impact your chances for both admission and funding.

FURTHER INFORMATION ABOUT COMPLETING THE ADMISSIONS FORMS:

The Machine Learning Group is based in the Department of Engineering, not Computer Science.

We will assess your application on three criteria:

1 Academic performance (ensure evidence for strong academic achievement, e.g. position in year, awards, etc.) 2 references (clearly your references will need to be strong; they should also mention evidence of excellence as quotes will be drawn from them) 3 research (detail your research experience, especially that which relates to machine learning)

You will also need to put together a research proposal. We do not offer individual support for this. It is part of the application assessment, i.e. ascertaining whether you can write about a research area in a sensible way and pose interesting questions. It is not a commitment to what you will work on during your PhD. Most often PhD topics crystallise over the first year. The research proposal should be about 2 pages long and can be attached to your application (you can indicate that your proposal is attached in the 1500 character count Research Summary box). This aspect of the application does not carry a huge amount of weight so do not spend a large amount of time on it. Please also attach a recent CV to your application too.

INFORMATION ABOUT THE CAMBRIDGE-TUEBINGEN PROGRAMME:

We also offer a small number of PhDs on the Cambridge-Tuebingen programme. This stream is for specific candidates whose research interests are well-matched to both the machine learning group in Cambridge and the MPI for Intelligent Systems in Tuebingen. For more information about the Cambridge-Tuebingen programme and how to apply see here . IMPORTANT: remember to download your application form before you submit so that you can send a copy to the administrators in Tuebingen directly . Note that the application deadline for the Cambridge-Tuebingen programme is noon, 5th December, 2023, CET.

What background do I need?

An ideal background is a top undergraduate or Masters degree in Mathematics, Physics, Computer Science, or Electrical Engineering. You should be both very strong mathematically and have an intuitive and practical grasp of computation. Successful applicants often have research experience in statistical machine learning. Shortlisted applicants are interviewed.

Do you have funding?

There are a number of funding sources at Cambridge University for PhD students, including for international students. All our students receive partial or full funding for the full three years of the PhD. We do not give preference to “self-funded” students. To be eligible for funding it is important to apply early (see https://www.graduate.study.cam.ac.uk/finance/funding – current deadlines are 10 October for US students, and 1 December for others). Also make sure you tick the box on the application saying you wish to be considered for funding!

If you are applying to the Cambridge-Tuebingen programme, note that this source of funding will not be listed as one of the official funding sources, but if you apply to this programme, please tick the other possible sources of funding if you want to maximise your chances of getting funding from Cambridge.

What is my likelihood of being admitted?

Because we receive so many applications, unfortunately we can’t admit many excellent candidates, even some who have funding. Successful applicants tend to be among the very top students at their institution, have very strong mathematics backgrounds, and references, and have some research experience in statistical machine learning.

Do I have to contact one of the faculty members first or can I apply formally directly?

It is not necessary, but if you have doubts about whether your background is suitable for the programme, or if you have questions about the group, you are welcome to contact one of the faculty members directly. Due to their high email volume you may not receive an immediate response but they will endeavour to get back to you as quickly as possible. It is important to make your official application to Graduate Admissions at Cambridge before the funding deadlines, even if you don’t hear back from us; otherwise we may not be able to consider you.

Do you take Masters students, or part-time PhD students?

We generally don’t admit students for a part-time PhD. We also don’t usually admit students just for a pure-research Masters in machine learning , except for specific programs such as the Churchill and Marshall scholarships. However, please do note that we run a one-year taught Master’s Programme: The MPhil in Machine Learning, and Machine Intelligence . You are welcome to apply directly to this.

What Department / course should I indicate on my application form?

This machine learning group is in the Department of Engineering. The degree you would be applying for is a PhD in Engineering (not Computer Science or Statistics).

How long does a PhD take?

A typical PhD from our group takes 3-4 years. The first year requires students to pass some courses and submit a first-year research report. Students must submit their PhD before the 4th year.

What research topics do you have projects on?

We don’t generally pre-specify projects for students. We prefer to find a research area that suits the student. For a sample of our research, you can check group members’ personal pages or our research publications page.

What are the career prospects for PhD students from your group?

Students and postdocs from the group have moved on to excellent positions both in academia and industry. Have a look at our list of recent alumni on the Machine Learning group webpage . Research expertise in machine learning is in very high demand these days.

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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

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
• Biotechnology MPhil
• Research in Agri-Food Robotics EPSRC CDT PhD
• Biological Science (Babraham Institute) PhD

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