UKRI Centre for Doctoral Training in Artificial Intelligence, Machine Learning & Advanced Computing

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The UKRI CDT in Artificial Intelligence, Machine Learning and Advanced Computing provided 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) played an essential role, as did engagement with external partners, which included large international companies, locally based start-ups and SMEs, and government and Research Council partners.

The CDT was 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 provided bespoke support via Research Software Engineers and access to HPC facilities in a coordinated fashion. We worked closely together with the STFC CDT on Data-Intensive Science.

All cohorts have been recruited. No further funding for studentships is available.

Training

The programme consisted 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 was embedded throughout and included a short-term placement in Year 2 and a further 6-month placement across Years 2/3. Transferable skills training was 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 and Events pages.

Research

Our doctoral training programme was constructed around three research themes:

• T1: data from large science facilities (particle physics, astronomy, cosmology)
• T2: biological, health and clinical sciences (medical imaging, electronic health records, bioinformatics)
• T3: novel mathematical, physical, and computer science approaches (data, hardware, software, algorithms)

While the themes are diverse as academic disciplines, in our CDT they are linked through the use of AI, machine learning and advanced computing methods. Therefore, a crucial role is played by knowledge exchange across themes via cohort training, joint supervision, peer-to-peer interaction and student mentoring. Research project are embedded within one of the themes, with supervisory support across themes, to develop new synergies. More details can be found on the Research page.

Fully funded PhD positions

Fully funded PhD positions were available for students with a strong interest and aptitude in computational science and in one of our research themes. Positions were funded for 4 years, including the placements with the external partners. Considerable funding was available for training, workshop and conference support, as well as for a laptop and other computational resources. The CDT has recruited 5 cohorts, with the aim of a minimum of 11 PhD students per cohort. The first, second, third, fourth, and fifth cohorts have started in October 2019, 2020, 2021, 2022, and 2023 respectively. The final cohort aims to graduate in the autumn of 2027.