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cambridge university statistics phd

Research in DPMMS is actively undertaken across a range of modern mathematics.

The pages for individual members of DPMMS give information about each person's research interests.

DPMMS also hosts:

  • The Cambridge Mathematics of Information in Healthcare Hub ( CMIH) 
  • Cambridge Mathematics of Information (Centre for Doctoral Training)

Postdoctoral Opportunities

  • Postdoc opportunities at DPMMS
  • Postdocs of Cambridge Society (PdOC)

Research Students

  • Information for new PhD students
  • Information for current Postgraduate Students

Special Lectures and Events

Regular Seminars

Annual Lectures

  • The  Mordell Lecture is given annually by an invited speaker for a research-level audience
  • The  Rouse Ball Lecture is sponsored jointly with DAMTP  but aimed at undergraduates.
  • The  Peter Whittle  Lecture is given annually by an invited speaker in the field of Statistics  
  • DPMMS Colloquia

Research conferences 

  • Archive of past events

Thesis Archive

DPMMS maintains a PhD thesis archive on Apollo

Guidance on adding new theses to the archive is available .

Related sites

  • Statistical Laboratory
  • Faculty of Mathematics
  • Isaac Newton Institute for Mathematical Sciences

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What are my chances of getting in?

This is one of the most frequently asked questions about applying to Cambridge. 

On average across all subjects, we typically receive six applications per place, but naturally there is some variation between courses. 

College choice or making an open application does not affect your chance of being made an offer because we compare all applicants for each subject before selection decisions are finalised.

Directors of Studies in each subject meet to discuss the overall standard of applications so they can see how their own College’s applicants compare. Then, the best applicants who could not be accepted by their original College can be made an offer by another College through the ‘winter pool’. 

The pool results in many students (897 in the case of the 2023 cycle - nearly 20 per cent of all offers made) receiving an offer from a College other than the one they applied to. This means that success rates are very similar from College to College.

The University and Colleges are committed to offering admission to students of the highest academic ability and potential, and would rather admit a strong applicant from the pool than a weaker applicant who applied directly to them (or who was allocated through the open application system).

NB: 'Admissions cycle' refers to the UCAS cycle in which applications were considered. For example, the '2024 cycle' refers to applications made from September 2023 onwards, for courses starting in October 2024 or deferred entry in 2025.

Admission statistics

For a snapshot of our application and admissions statistics, please use the graph generator below. More detailed information about the range of data we hold about undergraduate applications is available on Tableau, where you can browse and filter the information you're interested in.

View Tableau data

Graph generator

To view the graph, select from the options below and click 'Show graph'. 

Generate a graph showing undergraduate application and admissions statistics based on a variety of criteria, including College and course. Please note:

  • 'Acceptances through Summer Pool' includes applicants accepted via the August Reconsideration Pool, as well as offer-holders accepted via the Summer Pool by a College other than their offering College.
  • The source data for these graphs was last refreshed on 14 February 2024.

Undergraduate Admissions Statistics

PDF icon

Applications, Offers and Acceptances by UCAS Apply Centre

Archived reporter statistics.

Detailed statistics from previous admissions cycles (up to 2010) are available in the  Cambridge University Reporter Special Issues .

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Your Programmes

University of Cambridge

PhD Pure Mathematics and Mathematical Statistics

1 in 5 applicants to this programme received an offer.

Data shown above is for entry in academic year 2021/22 (sources) .

Previous Years

Data sources.

  • FOI Request by Albert Warren.
  • FOI Request by Ash Rizwan. January 2017.
  • FOI Request by Lai Yinsheung. August 2022.

The acceptance rate , or offer rate, represents the fraction of applicants who received an offer. Note that this will be generally lower the acceptances rates (acceptances divided by applicants) published by many other sources. This article explains it in more detail. The acceptances generally indicate the number of offer holders who accepted the offer and fulfilled its conditions. For some universities, however, it denotes the number of applicants who accepted the offer, regardless of whether they subsequently met its conditions.

Data Reliability

Unless otherwise noted, the data presented comes from the universities and is generally reliable. However, some of the differences between years and/or courses may be due to different counting methodologies or data gathering errors. This may especially be the case if there is a sharp difference from year to year. If the data does not look right, click the "Report" button located near the top of the page.

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Prediction markets can be used to estimate odds of a future event. You can create a prediction market on any topic, including your personal university admission chances.

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  • Internal wiki

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.

University of Cambridge

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Sociology Seminar

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

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

The Department of Sociology University of Cambridge Free School Lane Cambridge CB2 3RQ

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Wentian Huang - “Nonparametric and semiparametric approaches to functional data modeling”

Dissertation Advisor: David Ruppert

Initial job placement: Ernst & Young

Binh Tang - “Deep probabilistic models for sequential prediction”

Dissertation Advisor: David Matteson

Initial job placement: Amazon

Yi Su - “Off-policy evaluation and learning for interactive systems"

Dissertation Advisor: Thorsten Joachims

Initial job placement: Berkeley (postdoc)

Ruqi Zhang - “Scalable and reliable inference for probabilistic modeling”

Dissertation Advisor: Christopher De Sa

Jason Sun - “Recent developments on Matrix Completion"

Dissertation Advisor: Martin Wells

Initial job placement: LinkedIn

Indrayudh Ghosal - “Model combinations and the Infinitesimal Jackknife : how to refine models with boosting and quantify uncertainty”

Dissertation Advisor: Giles Hooker

Benjamin Ryan Baer - “Contributions to fairness and transparency”

Initial job placement: Rochester (postdoc)

Megan Lynne Gelsinger - “Spatial and temporal approaches to analyzing big data”

Dissertation Advisor: David Matteson and Joe Guinness

Initial job placement: Institute for Defense Analysis

Zhengze Zhou - “Statistical inference for machine learning : feature importance, uncertainty quantification and interpretation stability”

Initial job placement: Facebook

Huijie Feng - “Estimation and inference of high-dimensional individualized threshold with binary responses”

Dissertation Advisor: Yang Ning

Initial job placement: Microsoft

Xiaojie Mao - “Machine learning methods for data-driven decision making : contextual optimization, causal inference, and algorithmic fairness”

Dissertation Advisor: Nathan Kallus and Madeleine Udell

Initial job placement: Tsinghua University, China

Xin Bing - “Structured latent factor models : Identifiability, estimation, inference and prediction”

Dissertation Advisor: Marten Wegkamp and Florentina Bunea

Initial job placement: Cambridge (postdoc), University of Toronto

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Finding a DPMMS Supervisor

Before applying to the DPMMS PhD , you are encouraged to discuss informally with possible supervisors. It will help our consideration of your application to know with whom you are interested in working and in what fields. This does not necessarily have to be narrowed down to a single supervisor or research area. 

Potential supervisors for the four year PhD, Cambridge Mathematics of Information (CMI), can be found here . 

Contact details may be found on each supervisor's webpage. You are encouraged to make initial contact by email, and to provide a CV and brief explanation of your areas of interest.

Algebra Algebraic Geometry Analysis and Partial Differential Equations Combinatorics Differential Geometry and Topology Foundations Information and Finance Number Theory Probability Statistics

Algebraic Geometry

Analysis and partial differential equations, combinatorics, differential geometry and topology, foundations, information and finance, number theory, probability.

PhDs in Statistics within the Statistical Laboratory cover a wide range of contemporary challenges in the subject, from theoretical and methodological innovations, to computational developments and applications in many different domains. Prospective applicants are encouraged to make contact with a potential supervisor or supervisors prior to submitting their documents. List of PhD supervisors in Statistics who are willing to consider new students for October 2023 admission:

Forthcoming Seminars

  • DAMTP Seminars
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News, Announcements and Events

cambridge university statistics phd

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  1. PhD in Pure Mathematics and Mathematical Statistics

    PhD in Pure Mathematics and Mathematical Statistics. This course is a three to four year programme culminating in the submission and examination of a single research thesis. Students joining the course will often have completed prior study at a level comparable to our Part III (MMath/MASt) course and many have postgraduate experience.

  2. PhD in Pure Mathematics and Mathematical Statistics

    Our students, therefore, begin their PhD research with a good understanding of advanced material, which they build on in various ways throughout the course of their PhD studies. Structure of the PhD Students are required to undertake a minimum of nine full-time terms of research (ie three years). Students are not registered for the PhD in the ...

  3. Department of Pure Mathematics and Mathematical Statistics

    Thesis Archive. DPMMS maintains a PhD thesis archive on Apollo. Guidance on adding new theses to the archive is available . Department of Pure Mathematics and Mathematical Statistics. Centre for Mathematical Sciences. Wilberforce Road. Cambridge. CB3 0WB. [email protected].

  4. Index

    The Statistical Laboratory is located in Pavilion D of the Centre for Mathematical Sciences. It is sub-department of the Department of Pure Mathematics and Mathematical Statistics, which in turn is part of the Faculty of Mathematics.We have about 35 members, made up of permanent staff, post-docs, and post-graduate students.Our interests cover a broad range of statistics, probability and ...

  5. Postgraduate Study in Mathematics

    The Faculty of Education offers. a Mathematics Postgraduate Certificate in Education (PGCE) for those wishing to train as secondary-school teachers; specialised masters courses in mathematics education. Faculty of Mathematics, Wilberforce Road, Cambridge CB3 0WA, United Kingdom. Contact us.

  6. PhD in Pure Mathematics and Mathematical Statistics

    PhD in Pure Mathematics and Mathematical Statistics. This is a three year research programme culminating in submission and examination of a single research thesis. Students joining the course will often have completed prior study at a level comparable to our Part III (MMath/MASt) course and many have postgraduate experience.

  7. University of Cambridge Statistics PhD Projects, Programmes ...

    The UKRI AI Centre for Doctoral Training (CDT) in Decision Making for Complex Systems is a joint CDT between The University of Manchester and the University of Cambridge. Read more. Supervisor: Dr W Handley. 31 March 2024 PhD Research Project Competition Funded PhD Project (Students Worldwide) 1. Find a PhD is a comprehensive guide to PhD ...

  8. People

    Statistical Laboratory Centre for Mathematical Sciences Wilberforce Road Cambridge CB3 0WB [email protected]

  9. Core Statistics

    About the Authors. Based on a starter course for beginning graduate students, Core Statistics provides concise coverage of the fundamentals of inference for parametric statistical models, including both theory and practical numerical computation. The book considers both frequentist maximum likelihood and Bayesian stochastic simulation while ...

  10. Application statistics

    Admission statistics. For a snapshot of our application and admissions statistics, please use the graph generator below. More detailed information about the range of data we hold about undergraduate applications is available on Tableau, where you can browse and filter the information you're interested in. View Tableau data.

  11. Statistics and Operational Research

    Bayesian Statistics. Definitions, examples and comparisons with MLEs. You can use the following exercises to check your present level and to guide your study. Part Ib Statistics Example Sheet 1 (2014/15) Q3, 8, 9, 10; Part Ib Statistics Example Sheet 2 (2014/15) Q1, 2; Part Ib Statistics Example Sheet 3 (2014/15) Q1, 4, 5, 9; Useful books and ...

  12. PhD Pure Mathematics and Mathematical Statistics

    🎓 University of Cambridge acceptance rates and statistics for PhD Pure Mathematics and Mathematical Statistics for the years 2014, 2016, 2017, 2018, 2019, 2020 ...

  13. Doctor of Philosophy (PhD)

    The degree of Doctor of Philosophy (PhD) is the University's principal research degree for graduate students and is available in all faculties and departments. A Cambridge PhD is intellectually demanding and you will need to have a high level of attainment and motivation to pursue this programme of advanced study and research.

  14. PhD Programme in Advanced Machine Learning

    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 ...

  15. The PhD

    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 ...

  16. PDF GRADUATE admissions statistics

    From the total number of applications (30,321), 48.2% of applicants were female, 50.8% were male, and 1.0% applicants reported their Gender as 'Other' or 'Unknown'. 5 Admissions data by Citizenship excludes applications and Offers from programmes admitted by the Judge Business School (MBA,MFin, eMBA and Macc).

  17. 2021

    Dissertation Advisor: Marten Wegkamp and Florentina Bunea. Initial job placement: Cambridge (postdoc), University of Toronto. Wentian Huang - "Nonparametric and semiparametric approaches to functional data modeling" Dissertation Advisor: David Ruppert Initial job placement: Ernst & Young Binh Tang - "Deep probabilistic models for ...

  18. Finding a DPMMS Supervisor

    Potential supervisors for the four year PhD, Cambridge Mathematics of Information (CMI), can be found here . Contact details may be found on each supervisor's webpage. You are encouraged to make initial contact by email, and to provide a CV and brief explanation of your areas of interest. Algebra.