university of cambridge phd mathematics

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Department of Applied Mathematics and Theoretical Physics

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• Professor David Crighton
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• PhD in Mathematics of Information
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Research in DAMTP is loosely organised into eight broad subject areas:

Applied and Computational Analysis

• Astrophysics

Fluid and Solid Mechanics

Mathematical biology.

• Quantum Information
• High Energy Physics

General Relativity and Cosmology

The boundaries between the areas are not rigid and evolve with time. Many members of staff contribute to more than one area and this is regarded as a key factor in the continuing success of DAMTP. Research in each of the subject areas involves collaboration with strong groups nationally and internationally, and participation in numerous interdisciplinary projects and programmes.

Applied and Computational Analysis (ACA) at DAMTP spans a wide range of themes in partial differential equations, numerical analysis, dynamical systems and integrable systems. Its underlying organising principle is an inquiry into issues of interest in applications of mathematics and forging tools and methodology that are relevant in applications.

• Cantab Capital Institute for the Mathematics of Information
• Numerical Analysis
• Cambridge Centre for Analysis (Doctoral Training Centre)
• Cambridge Image Analysis
• Applied Functional and Harmonic Analysis
• Dr Maria Bruna
• Professor Colm-Cille Patrick Caulfield
• Professor Nilanjana Datta
• Professor Hamza Fawzi
• Professor Anders Christian Hansen
• Professor Adrian Kent
• Professor Paul Linden
• Professor Nigel Peake
• Professor Carola Bibiane Schönlieb
• Dr Alexei Shadrin
• Professor Edriss S. Titi

Researcher:

• Dr Kweku Abraham
• Dr Ander Biguri
• Dr Nicolas Boulle
• Zhongying Deng
• Dr Sören Dittmer
• George Rafael Domenikos
• Moshe Eliasof
• Dr Carlos Esteve-Yagüe
• Dr Julian Gilbey
• Ms Tamara Großmann
• Dr Michael Roberts
• Dr Bogdan Roman
• Dr Ferdia Sherry
• Dr Orsola Rath Spivack
• Shengding Sun
• Dr Jongmin Yu
• Mary Chriselda Antony Oliver
• Georgios Batzolis
• Simon Carlson
• Willem Diepeveen
• Holly Houliston
• Daniel Kreuter
• Wallace Eugene Peaslee
• Christina Runkel
• Jan Stanczuk
• Hong Ye Tan
• Samuel Tull
• Lipei Zhang

Professional and Support Staff:

• Mrs Zvezda Woodhouse

Emeritus Staff:

• Professor Thanasis Fokas
• Professor Arieh Iserles
• Dr Anna Breger
• Dr Priscilla Canizares
• Dr Jovita Lukasik
• David Oliver Cortadellas

College Teaching Officer:

• Dr Anthony Charles Lewis Ashton

• Professor Henrik Nils Latter
• Professor Gordon Ogilvie
• Professor Roman Rafikov
• Dr Mattias Brynjell-Rahkola
• Dr Giulio Del Zanna
• Roger Pierre Dufresne
• Dr Loren E Held
• Thomas Jannaud
• Samuel Turner
• Joshua Jonathan Brown
• Amelia Jane Cordwell
• Thomas Daggitt
• Stan DeLaurentiis
• Eva Deliporanidou
• Nathan Malo Titouan Magnan
• Matt Roberts
• Professor Douglas Gough
• Dr Helen Elizabeth Mason
• Professor Michael McIntyre
• Professor H.Keith Moffatt
• Professor John Papaloizou
• Professor Michael Richard Edward Proctor

This extended group addresses the science of atmosphere, cryosphere, ocean and solid Earth. DAMTP has been active in these areas since its formation in 1959, largely through staff who combine interests in fundamental fluid or solid mechanics with geophysical applications. As the relevant fundamental areas have matured DAMTP staff have naturally broadened their research further into application areas or, in some cases, have played major roles in establishing new 'fundamental' areas, such as the fluid mechanics of solidification and freezing.

• Atmosphere-Ocean Dynamics
• Theoretical Geophysics
• Professor Peter Howard Haynes
• Dr Duncan Robin Hewitt
• Professor John Ronald Lister
• Professor Jerome Neufeld
• Professor John Ryan Taylor
• Professor Michael Grae Worster
• Dr Amir Atoufi
• Dr Alison Donna Ming
• Joséphine Anselin
• Emma Bouckley
• Isaac P. Brown
• Matt Davison
• Jennifer Dingwall
• Rachel Furner
• Shi-Wei Jian
• Charles Powell
• Elvinas Ribinskas
• Jago Strong-Wright
• Wren Stuart
• Sophie Tobin
• Wenzhong Wang
• Joseph Webber
• Dr Mark Hallworth
• Professor Herbert Huppert
• Zoe Gillett
• Paul Pruzina
• Kasturi Sanjiv Shah
• Chris Warner

The research of this large group extends through fluid mechanics, granular flow and solid mechanics, and an extremely wide range of applications. Members of this group are active in experimental work in the GK Batchelor Laboratory. Overall the main approach to solving scientific and industrial problems is to seek physical understanding through construction and (often asymptotic) analysis of the simplest mathematical model that is consistent both with the laws of physics and with experimental observation.

• Astrophysical Fluid Dynamics
• Biological Physics & Mechanics
• Environmental and Industrial Fluid Dynamics
• G.K. Batchelor Laboratory
• High-Reynolds-Number Fluid Flow
• Quantum Fluids
• Soft Matter
• Solid Mechanics
• Waves Group
• Professor David Abrahams
• Dr Ronojoy Adhikari
• Professor Natalia Berloff
• Professor Michael Cates
• Professor Stuart Bruce Dalziel
• Professor Ray Goldstein
• Professor Robert Jack
• Professor Rich Kerswell
• Professor Eric Jean-Marie Lauga
• Professor Ben Simons
• Dr Lorna Jane Ayton
• Dr Miguel Beneitez Galan
• Dr Rajesh Bhagat
• Dr Jane Chui
• Dr George Fortune
• Dr Rosalba Garcia Millan
• Siddharth Ghosh
• Dr Steph Höhn
• Dr Catherine Kamal
• Dr Adrien Lefauve
• Dr Kyriacos Leptos
• Dr Ivan Lobaskin
• Dr. Sarah A.M. Loos
• Matthew Nethercote
• Dr Adriana Irma Pesci
• Mr Nicolaos Petropoulos
• Dr Praneet Prakash
• Dr Maria Cristina Rodriguez Rivero
• Dr Mark Spivack
• Samuel James Bradford
• Calum Brown
• Gergely Buza
• Rami Cassia
• Rosie Cates
• James Cummins
• Filippo De Luca
• Alistair Hales
• Joel Hochstetter
• Joseph Holey
• Pyae Hein Htet
• Georgia Ioannou
• Laura Irvine
• Airat Kamaletdinov
• Zhixuan Liu
• Arnab Mallik
• Benjamin McMillan
• Shiza Batool Naqvi
• Balázs Németh
• Stefan Nixon
• Mohammadreza Noormandipour
• William Oliver Oxley
• George Poole
• Janik Schüttler
• John William Severn
• Anand Srinivasan
• Marvin Syed
• Marco Federico Vona
• Richard, Zhipeng Wang
• Andrew Zhou
• Mrs Hannah Edwards
• Dr Katherine Roberts
• Professor Edward John Hinch
• Professor John Martin Rallison
• Professor Peter Wadhams
• Tal Agranov
• Anne Bernheim
• Yuxuan Chen
• Dr Mingnan Ding
• Dario Klingenberg
• Valentin Kunz
• Dr John Denis Sherwood
• Michael te Vrugt
• Mohamed Warda
• Robert Hunt

Research areas include biomechanics, biological physics, epidemiology and computational neuroscience. Part of the group plays a major role in the CCBI which is a recent cross-School initiative, hosted in DAMTP, to bring together the exceptional strengths of Cambridge in medicine, biology, mathematics and the physical sciences.

• Computational Biology
• Disease Dynamics
• Machine Learning and Artificial Intelligence
• Cambridge Centre for AI in Medicine (CCAIM)
• Professor Stephen John Eglen
• Professor Julia Rose Gog
• Professor Gos Micklem
• Professor Mihaela van der Schaar
• Dr Yuan Huang
• Yichen (Kelly) Chen
• Maria Alegria Gutierrez Guillen
• Zhiyuan Desmond Lai
• Professor Timothy John Pedley
• Mr Alex Dunn
• Dr Petra Klepac

Activities of this group are focused in the CQIF. Research topics include quantum cryptography (a particular strength), quantum computing algorithms, quantum information theory, quantum control, and modelling the implementation of quantum computers in physical systems.

• Professor Benjamin Beri
• Angela Capel Cuevas
• Professor Frank Verstraete
• Davi De Castro Silva
• Aditya Jain
• Dr Damián Pitalúa-Garcia
• Dr Subhayan Roy Moulik
• Dr Sergii Strelchuk
• Carolin Christina Wille
• Bjarne Bergh
• Mitchell Chiew
• George Cowperthwaite
• Joshua Cudby
• Samuel Fedida
• Campbell McLauchlan
• Oliver O'Brien
• Wilfred Salmon
• Satvik Singh
• Professor Richard Jozsa
• Dr Boris Groisman

This is one of two large groups in theoretical physics, the other being the General Relativity and Cosmology group. Advances on several fronts have led to a breakdown of the historical divisions between the two groups and several staff members are members of both. The group is active in Particle Physics Phenomenology, Quantum Field Theory, String Theory, and Lattice Field Theory. (Particle physics related to the Big Bang and very early universe are covered under General Relativity and Cosmology.)

• Professor Ben Allanach
• Dr Alejandra Castro Anich
• Professor Nicholas Dorey
• Professor Maciej Dunajski
• Dr Jonathan Mark Evans
• Professor Sean Alexander Hartnoll
• Professor Enrico Pajer
• Professor Fernando Quevedo
• Professor Harvey Reall
• Professor Jorge Eduardo Pinto Santos
• Professor David Benjamin Skinner
• Professor David Michael Addis Stuart
• Professor Christopher Thomas
• Professor David Tong
• Professor Maria Ubiali
• Dr Aron Wall
• Professor Matthew Bowen Wingate
• Dr Hannah Banks
• Mr Mark Costantini
• Dr Marine De Clerck
• Dr Jackson Fliss
• Dr Nico Gubernari
• Mr Elie Hammou
• Dr Bob Knighton JR
• Dr Nelson Lachini
• Dr Luca Mantani
• Dr Rishi Talwar Mouland
• Dr Ronak Soni
• Dr David Wilson
• Dr Bernardo Zan
• Santiago Agüi Salcedo
• Matthew John Blacker
• Robert Bourne
• Alex Colling
• Maxime Jean Hubert Gadioux
• Simon Heuveline
• Christopher Hughes
• Khoi Le Nguyen Nguyen
• Eetu Aleksi Loisa
• Nathan Matthew McStay
• Manuel Morales Alvarado
• Veronica Pasquarella
• Mario Ramos Hamud
• Paul Luis Röhl
• Ayngaran Thavanesan
• Gonzalo Villa
• Ms Amanda Stagg
• Professor Anne Christine Davis
• Professor Ian Drummond
• Professor Michael Green
• Professor Ronald Raymond Horgan
• Professor Peter Landshoff
• Dr Alan James Macfarlane
• Professor Nicholas Stephen Manton
• Professor Hugh Osborn
• Professor Malcolm John Perry
• Professor John Taylor
• Professor Paul Kingsley Townsend
• Dr Ruth Margaret Williams
• Dr Ben Gripaios
• Laurens Lootens
• Dr Alex Mitov
• Sir Martin Rees
• Dr Watse Sybesma
• Dr Ron Reid-Edwards

The interests and membership of this large group overlap with those of the High Energy Physics group. It hosts the COSMOS supercomputer, a national facility dedicated to studies of early Universe physics and the new Centre for Theoretical Cosmology (CTC). Despite its infancy the CTC has already hosted several conferences and workshops, including 'The Very Early Universe; 25 years on'. The group is active in numerical relativity, supergravity, discrete gravity, M-theory/string theory and cosmology.

• Relativity & Gravitation
• Cambridge Centre for Theoretical Cosmology (CTC)
• Professor Anthony David Challinor
• Dr Miles Cranmer
• Dr James Robert Fergusson
• Professor Jonathan Gair
• Professor Edward Paul Scott Shellard
• Professor Blake Sherwin
• Professor Ulrich Sperhake
• Thomas Colas
• Daniela Cors Agullo
• William Richard Coulton
• Dr Amelia Louise Drew
• Dr Carlos Duaso Pueyo
• Steven Thomas Gratton
• Dr Fiona McCarthy
• Dr Francesco Muia
• Dr Isobel Romero-Shaw
• Owain Salter Fitz-Gibbon
• Dr Manus Visser
• Dr Zvonimir Vlah
• Dr Dong-Gang Wang
• Irene Abril Cabezas
• David Gwilym Baker
• William Biggs
• Johnnie Crump
• Iain Davies
• Yaniv Donath
• Carmen Embil Villagra
• Tamara Evstafyeva
• Gerrit Simon Farren
• Ericka Ann Florio
• Tamanna Jain
• Istvan Kadar
• Yoann Levis Launay
• Mang Hei Gordon Lee
• Gareth Marks
• Ciaran Arthur McCulloch
• Alexander Dimitri Miranthis
• Seppe Staelens
• Petar Suman
• Monica Tapia del Moral
• Bowei Zhang
• Juliana Kwan
• Mr James Parke
• Dr Peter D'Eath
• Professor Gary Gibbons
• Alexander Soloviev
• Dr Yoav Zigdon
• Irena Borzym
• Matthias Doerrzapf
• Peter O'Donnell

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The Department of Pure Mathematics and Mathematical Statistics (DPMMS) at Cambridge has a large number of faculty, postdocs and graduate students, with active research groups across the spectrum of mathematics. Strengths include:

• algebra (group theory, representation theory);
• algebraic geometry (higher-dimensional algebraic geometry, algebraic cycles, abelian varieties, mirror symmetry, geometric aspects of representation theory);
• analysis (geometric analysis, PDEs, mathematical relativity, discrete analysis);
• category theory (logic, proof theory, topos theory, higher-dimensional category theory)
• combinatorics (random structures, combinatorial number theory, Ramsey theory, graph theory)
• differential geometry (dynamics, low-dimensional topology and knot theory, gauge theory, Riemannian geometry, symplectic topology);
• number theory (algebraic number theory, Iwasawa theory, computational number theory);
• probability and statistics (including financial mathematics, operational research, stochastic methods, transport and networking problems).

More detailed information can be found on other departmental webpages. If you have interests in these areas, particularly in the areas of expertise of departmental members, consider coming to Cambridge for a postdoc. (Related research groups at Imperial College, London and at Oxford are close, and there are close links -- including shared participation in some seminars -- with these departments, which adds to the richness of the local mathematical community.) There are various kinds of postdoc available, suitable for people at different levels, and requiring different application procedures. Some more information on each is available below.

• HERCHEL-SMITH POSTDOCTORAL RESEARCH FELLOWSHIPS: A Fellowship in Mathematics is advertised as part of a University wide scheme. We expect to appoint one or more positions each year. The postdocs are tenable for 3 years and are on a competitive salary scale. The positions carry no teaching obligations, and are purely intended for research, although opportunities to give Masters-level or graduate-level courses are available. Applications from all areas of pure mathematics will be considered. Applicants should be towards the end of their PhD or within the first 2-3 years of postdoctoral research. Further particulars will be given on the departmental vacancies page when applications are open, which is typically around late October.
• COLLEGE RESEARCH FELLOWSHIPS: These are prestigious postdocs, funded directly by the Cambridge Colleges. Holders of the positions are fully integrated into DPMMS, with office space in the department as well as their college. The precise details of these positions vary from college to college, and their availability varies from year to year. Typically, colleges offer up to 4 positions, for a tenure of 3 or 4 years. All positions are research positions, with few or minimal teaching obligations; the positions are associated with membership of a college, and typically come with accommodation and other perquisites. In some but not all cases there may be criteria of eligibility (e.g. citizen of an EU member state, or graduand of a UK university, etc). All such positions are advertised in the Cambridge University Reporter: www.admin.cam.ac.uk/reporter/current/weekly/ ; check regularly to see if there are openings in Mathematics. Note that although these positions are competitive across subjects, mathematicians are often successful: in a typical year there are 3 or more pure mathematicians appointed to such positions from the various colleges. For a further view see Professor Körner's unofficial
• Guide for Mathematicians Seeking a Cambridge Research Fellowship
• 1851 ROYAL COMMISSION RESEARCH FELLOWSHIPS: 2-year postdoctoral fellowships in mathematics and biological/physical sciences, which can be held at any UK university. Applicants should recently have completed or be about to complete a PhD: there are strict eligibility criteria (UK or Commonwealth national, or citizen of Ireland or Pakistan). Further information and application deadlines can be found here.
• MARIE-CURIE POST-DOCTORAL FELLOWSHIPS: 2 year research-only postdoctoral positions, funded by the EU (to a generous salary), available to EU nationals to work in a country which is neither the country of their PhD nor their home country. Open calls for applications -- which are often but not always present -- can be found with some effort via the website ; follow links for Individual Researchers. Marie-Curie grant applications are made jointly with the department, and are directly linked to the research of a specific member of faculty. The first stage in applying is to make contact with such a potential supervisor and discuss possible projects and establish whether or not there is support for and scope for a plausibly successful application.
• ROYAL SOCIETY UNIVERSITY RESEARCH FELLOWSHIPS: Unique 8 year research-only fellowships. These are suitable for outstanding young mathematicians who have completed their PhD and already done one postdoc. Applications must have emphatic support from DPMMS; if you are interested in applying, contact a member of the department in a related subject. Further information is available from their website :     The deadline is typically in very early November of the preceeding year. Results are only available in April, but who else is going to give you 8 years money with no obligations?

POSSIBILITIES NEARBY: Imperial College London is only an hour from Cambridge, also has outstanding research groups in various fields (including the geometry group led by Simon Donaldson), and we often travel to and from one another's seminars. Oxford is slightly further but by no means inaccessible. Why not try applying there too? More information can be found on the websites https://www.imperial.ac.uk/mathematics/research/opportunities/ , and www.maths.ox.ac.uk/ . Example opportunities include:

• Chapman Fellowships at Imperial
• Colleges at the University of Oxford also offer Junior Research Fellowships, details are usually available via the Gazette www.ox.ac.uk/gazette/ .

Related sites

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

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Centre for Quantum Information and Foundations

• Group Members
• Seminars and Events
• Part IB Quantum Mechanics
• Part II Quantum Information and Computation
• Part III Quantum Information, Foundations and Gravity
• Part III Quantum Computation
• Part III Quantum Information Theory

Graduate Applications

The CQIF includes four members of DAMTP Faculty, two affiliated members, and several senior researchers.

We always have to turn away some outstanding applicants: if you are considering applying to us you should also apply widely elsewhere. Applicants who are not UK citizens should also carefully consider the information about funding below, and note the very early deadlines for applications for funding from Foundations and Trusts. Applications to start a PhD in October 2022 will be considered from November 2021 onwards.

Successful applicants are likely to have a first class undergraduate degree in mathematics, physics or computer science, and should ideally also have an M.Sc. or equivalent qualification. Candidates considering applying directly from an undergraduate degree are encouraged to consider applying first to take Cambridge's one-year Masters-level course, the Master of Advanced Study in Mathematics (Part III of the Cambridge Mathematics Tripos). The course includes one or more lecture courses on aspects of quantum information and foundations, as well as courses on a wide variety of other topics in theoretical physics and pure and applied mathematics.

Applications from graduate students to research centres in DAMTP are handled by the Board of Graduate Studies in the first instance, and then administered by the department. Applications for PhD places should thus be made to the Board of Graduate Studies in the first instance, specifying an interest in working at the CQIF in DAMTP. The information needed can all be found on this page . Note that the timetable for applications has some very early application deadlines.

The University's admissions process is quite slow and, beyond the initial acknowledgment of receipt of your application, past experience suggests it could be as late as May before you hear any more from the University. Once the application process has started, your application can be tracked using your self-service account .

Applications for the Part III course should also be made to the Board of Graduate Studies. The information needed can be found on this page .

Our standard method of funding UK and EU graduate students is by grants from the UK Engineering and Physical Sciences Research Council. These are allocated by the department, mostly after the Part III results in mid to late June. EPSRC studentships provide full support for UK students, and cover tuition fees for EU students from outside the UK.

There are some other possible sources for funding (which are not generally restricted to EU students): for example the Gates Foundation, the Cambridge Commonwealth Trust, and a small number of the wealthier Cambridge Colleges. Decisions on these scholarships are made in May. Unfortunately (at least for us!), these funding sources are entirely outside our control or influence; in particular there is nothing we can do to get a decision from them sooner than May. Applications to these organisations and institutions need to be made separately. The University's Board of Graduate Studies web pages --- reached from the above-mentioned links --- have some information; anyone needing clarification or advice should contact either them or the relevant organisation. We have no independent sources of support for non-EU students.

While we try to be helpful where possible, there is normally little that we can add to the information given here. We cannot generally comment in advance on the chances of any individual application to the CQIF being successful or offer advice in putting together an application. Applicants may find it helpful, though, to look at the information on our group web pages, and especially useful to look at some of the recent papers of CQIF members, which can mostly be found on the quantum physics archive . (Some recent papers are also linked from CQIF members' personal pages on this site.)

We normally interview  selected candidates once applications have been reviewed: the timetable for these varies from year to year.

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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.

1 hr 28 min

13: Steve Furber on Cambridge, Acorn Computers and the University of Manchester Hearing your Future: The Coding your Future podcast

Meet Steve Furber. Steve graduated with a Bachelor of Arts degree in Mathematics from the University of Cambridge in 1974, followed by a PhD in aerodynamics in 1980 and a Master of Mathematics (MMath) belatedly awarded in 2010. After ten years working at Acorn Computers on the BBC Micro and its successor the ARM1, he was appointed Professor at the University of Manchester in 1990, where he led a variety of research projects over 33 years culminating in the arm-powered SpiNNaker project. As of 2023, there are more than 250 billion arm designed chips on the planet, 30 for every person currently alive. Each of these chips uses the same basic Reduced Instruction Set Computer (RISC) architecture pioneed in the ARM1. After a long and distinguished career, Steve retired in September 2023, when this episode was recorded. https://www.cdyf.me/steve

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MASt in Mathematics (Mathematical Statistics)

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Course closed:

Mathematics (Mathematical Statistics) is no longer accepting new applications.

This course is an application stream for the Master of Advanced Study (MASt) in Mathematics; students should apply to only one of the application streams for this course.

This course, commonly referred to as Part III, is a nine-month taught masters course in mathematics. It is excellent preparation for mathematical research and it is also a valuable course in mathematics and 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 Mathematical 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, or whether they applied through the Applied Mathematics (MASA), Pure Mathematics (MASP), Mathematical Statistics (MASS), or Theoretical Physics (MASTH) application stream.

There are around 280 Part III (MASt and MMath) students each year; almost all are in their fourth or fifth year of university studies. Each year the Faculty offers up to 80 lecture courses in Part III, covering an extensive range of pure mathematics, probability, statistics, applied mathematics and theoretical physics. They are designed to cover those advanced parts of the subjects that are not normally covered in a first-degree course, but which are an indispensable preliminary to independent study and research. Students have a wide choice of the combination of courses they take, though naturally, they tend to select groups of cognate courses. Examples classes and associated marking of (unassessed) example sheets are provided as complementary support to lectures.

As a taught masters course, the main emphasis is on lecture courses, and assessment is almost entirely based on written exams, which are normally taken at the end of the academic year starting in the last week of May, alongside a mathematical essay, normally due in early May. The standard graduation dates for successful candidates are usually in June and July.

Learning Outcomes

After completing Part III, students will be expected to have:

• studied advanced material in the mathematical sciences to a level not normally covered in a first degree;
• further developed the capacity for independent study of mathematics and problem-solving at a higher level; and
• undertaken an extended essay normally chosen from a list covering a wide range of topics.

Students are also expected to have acquired general transferable skills relevant to mathematics as outlined in the Faculty Transferable Skills Statement.

MASt students wishing to apply for a PhD at Cambridge must apply via the Postgraduate Admissions webpage for readmission by the relevant deadline. Details of entry requirements can be found in the relevant course listings on this site.

Applications to study in either of the Mathematics Departments will be considered on a case-by-case basis and offer of a place will usually include an academic condition based on Part III results.

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.

Departments

This course is advertised in the following departments:

• Faculty of Mathematics
• Department of Pure Mathematics and Mathematical Statistics

Key Information

9 months full-time, study mode : taught, master of advanced study, department of pure mathematics and mathematical statistics this course is advertised in multiple departments. please see the overview tab for more details., course - related enquiries, application - related enquiries, course on department website, dates and deadlines:, michaelmas 2024 (closed).

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

Funding Deadlines

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

Similar Courses

• Mathematics (Pure Mathematics) MASt
• Mathematics (Theoretical Physics) MASt
• Mathematics (Applied Mathematics) MASt
• Mathematics MPhil
• Pure Mathematics and Mathematical Statistics PhD

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