How to Apply

We expect to offer 10 fully-funded PhD studentships per year. Students with a strong background in computer science, mathematics, physics, or engineering are particularly encouraged to apply.

The CDT in Data Science is a 4-year programme at the University of Edinburgh: the first year provides Masters level training in the core areas of data science, along with a significant project. In years 2-4 students will carry out PhD research in data science, guided by PhD supervisors from within the centre.


There will be three application deadlines for PhD studentships beginning in September 2018:

  • 8th December 2017 – all applicants are encouraged to apply by this deadline for full consideration but this is the deadline for any overseas applicants
  • 26th January 2018 – all UK and EU applicants (see Funding below for definition of eligibility) are encouraged to apply by this deadline for full consideration
  • 16th March 2018* – any remaining UK and EU studentships will be allocated in the third round.

* Applications after the mid-March 2018 deadline can still be considered if places are still available, but are not guaranteed full funding consideration.

Industry collaboration PhD projects beginning in September 2018

The CDT in Data Science has two different types of studentships: a regular CDT studentship and a CDT studentship with a PhD project in collaboration with an industry partner. For a regular CDT studentship, students choose their PhD projects at the beginning of year 2 (after the MSc by Research); there are approximately 10 regular studentships available. For a PhD project in collaboration with an industry partner, students commit to a particular PhD project at the application stage.

Details of any available partner funded studentships will be posted here over the next few weeks with an application deadline of February 2018.

Last year, PhD studentships included:

  • Declarative Programming for Data Science / LogicBlox
  • Improving News Reader Experience with Online Journalism / FT
  • Improving Two-step Prediction Models in Consumer Research / Unilever

Open Days

The CDT's Open Days are opportunities to learn more about the programme, as well as the University of Edinburgh. Join us for in-person or virtual presentations and informal sessions to ask questions and discuss research opportunities.


Our fully funded PhD places are particularly competitive especially for those who are not UK resident. 

We also welcome applicants who are funded from other sources, such as awards from their home country or who are in receipt of industry/grant awards. These applications will be considered in addition to the allocated, fully funded places.  If you are able to provide your own funding, it is important that you make sure to state this in your application.


Entry Requirements

Before applying, please read the admissions information at the following links:


All applicants should ensure that their references are aware that applicants are applying for the full 1 year MSc by Research + 3 year PhD programme at the University of Edinburgh. Reference letters should include information about an applicant’s ability to undertake a PhD as well as an MSc by Research. We have a web page directed to referees to alert them to this. You might wish to send them a link to that page.

Letters of reference should be signed, dated, and on letter-headed paper:

Research Proposal

When you apply, you will be asked to include a personal statement statement where you can note your reasons for wishing to undertake PhD training in data science. This is separate from the research proposal.

A formal research proposal is required as part of the application process for the CDT in Data Science. In the research proposal you should indicate the area you believe would be of most interest to you for a PhD topic. If you are not familiar with the field, the proposal can be quite broad and your actual PhD project can differ from what you propose during your application. It is possible, and even likely, that you will change your interest during the course of the first year. Nevertheless, the motivation and research proposal are very important in our selection, so please pay attention to it! It is probably easier to attach a file  (either via “Upload a research proposal” or “Upload an unspecified document”) rather than to enter it all on the web form.

Before writing your proposal, you should visit the Research and Supervisor pages of our website. Both of these should give you a background on areas of research as well as current and potential research projects for postgraduate students.

There is no specific guidance for research proposals for applications to the CDT in Data Science; however, you may find it useful to refer to this document about writing a postgraduate research proposal for the University of Edinburgh.

CV / Résumé

Please include a CV or résumé with your application. You should upload this as a supporting document in EUCLID.

Research Area

Please provide a statement of your preferred research area if you can (e.g. Machine Learning, Databases etc) at the top of the Research Topic field on the application form. This does not commit you to work in this area, but helps us in ensuring the right people see your application.


To apply to the CDT in Data Science, use the standard University of Edinburgh website to apply for the programme called “Informatics: EPSRC Centre for Doctoral Training in Data Science: MSc by Research Data Science – 1 Year (Full-time)“. All CDT students should apply to this MSc programme as applications will automatically be considered for the full 1 year MSc by Research + 3 year PhD programme.

If you decide that you are more interested in other areas of computer science or informatics, the School of Informatics has many other postgraduate programmes available. Please see the School of Informatics pages about postgraduate study.

Please contact us if you have any queries.

Athena Swan Charter

Athena SWAN awards recognise and celebrate good practice on recruiting, retaining and promoting women in STEMM in academia.  The School of Informatics achieved a Silver Award in 2017.