Current PhD studentships
Please visit University's Jobs site for current studentship opportunities. The studentships are listed along with the name of the department hosting the studentship. 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.
Join the van der Schaar Lab
- We are creating cutting-edge machine learning methods and applying them to drive a revolution in healthcare.
- We have room for 1 or 2 outstanding machine learning Ph.D. students to join our elite group at the University of Cambridge in 2020.
- Follow on Twitter for the latest opportunities
- PhD position details https://www.vanderschaar-lab.com/join-the-van-der-schaar-lab/
Google PhD Fellowship 2020
- Closing date 1 September 2020
- Full details https://www.c2d3.cam.ac.uk/opportunities/restricted-call-google-phd-fellowship-2020
- The opportunity is open to full-time graduate students pursuing a PhD. Students must remain enrolled full-time in the PhD Programme for the duration of the Fellowship. Students cannot apply directly; they have to be nominated by their host university.
MPhil and PhD course relevant to data science
Particular MPhil and PhD courses relevant to data science are listed below. Please visit the relevant pages, and pay particular attention to the entry requirements and guidance for applicants there.
Do you need to brush up on your knowledge or learn something new before applying or attending an interview? Visit our Learning Materials page for learning resources.
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).
Erasmus exchange programme
Information about Erasmus exchange positions, including eligibility and how to apply, can be found on the Erasmus website.