The UKRI CDT in Artificial Intelligence, Machine Learning and Advanced Computing provides 4-year, fully funded PhD opportunities across the broad areas of particle physics and astronomy, biological and health, and mathematical and computer sciences. Training in AI, high-performance computing (HPC) and high-performance data analytics (HPDA) plays an essential role, as does engagement with external partners, which include large international companies, locally based start-ups and SMEs, and government and Research Council partners. 

The CDT is built upon longstanding research and training collaborations between the universities of Aberystwyth, Bangor, Bristol, Cardiff and Swansea. In addition, Supercomputing Wales and the University Computing Academies provide bespoke support via Research Software Engineers and access to HPC facilities in a coordinated fashion. Meet the Staff

Fully funded PhD positions are available for students with a strong interest and aptitude in computational science and in one of our research themes. Positions are funded for 4 years, including the placements with the external partners. The CDT will recruit 5 cohorts, with a minimum of 11 PhD students per cohort. The first cohort will start in October 2019.

The programme consists of a substantial training component in the first year, including cohort-based training in AI and computational methods, to establish a common base. Engagement with our external partners is embedded throughout and includes short-term placements in Year 1 and 2 and a 6-month placement in Year 3/4. Transferable skills training is delivered via residential meetings, at our annual CDT conference, and in cooperation with the Alan Turing Institute. More details can be found on the Training page.

Studentships at Swansea

We welcome applications by UK/Home and EU nationals. To qualify as a UK/Home applicant, prospective students must have been ordinarily resident in the UK for 3 years immediately prior to the start of the award, with no restrictions on how long they can remain in the UK. Residence in the UK that is solely for the purpose of education will only count towards these 3 years if the candidate is an EU national. 

To Apply

Please email your application to cdt-aimlac@swansea.ac.uk. Your application must include the following attachments in pdf form:
  • CV
  • Degree certificates and transcripts (if you are still an undergraduate, provide a transcript of results known to date)
  • A statement no longer than 2 pages of A4 in length that explains why you want to join our Centre. You should outline the sorts of AI and big data challenges you are interested in, which of the research themes (T1, T2, T3) has your prime interest and what area of research is most appealing to you (theoretical particle physics and cosmology, computational science, medical science, mathematical science, interdisciplinary research). You do not need to specify a detailed research plan at this time though as this will be shaped during the first year.
  • Completed research scholarship application form (Science) or research scholarship application form (Medicine)
  • Academic references - all scholarship applications require two supporting references to be submitted. Please ensure that your chosen referees are aware of the funding deadline (to be determined), as their references form a vital part of the evaluation process. Please either include these with your scholarship application or ask your referees to send them directly to cdt-aimlac@swansea.ac.uk
You should have an aptitude and ability in computational thinking and methods (as evidenced by a degree in physics and astronomy, medical science, computer science, or mathematics, for instance) including the ability to write software. The minimum entry requirement is a 2.1 undergraduate degree. For non-native English language speakers, an IELTS average score of 6.5 with no less than 6.0 in any element is required.
 
For general enquiries, you may also email cdt-aimlac @ swansea.ac.uk or contact the CDT Director Prof Gert Aarts directly.
 
To find out about studentships with one of our collaborators, visit http://cdt-aimlac.org/