Fully funded UKRI CDT Artificial Intelligence at Swansea University| How to Apply
This is a competitive scholarship scheme and three fully funded PhD scholarships are available at Swansea University.
Artificial Intelligence, Machine Learning and Advance Computing (AIMLAC) aims at forming the next generation of AI innovators across a broad range of STEMM disciplines. The CDT provides advanced multi-disciplinary training in an inclusive, caring and open environment that nurture each individual student to achieve their full potential. Applications are encouraged from candidates from a diverse background that can positively contribute to the future of our society.
The UK Research and Innovation (UKRI) fully-funded scholarships cover the full cost of tuition fees, a UKRI standard stipend of £17,668 per annum and additional funding for training, research and conference expenses.
The scholarships are open to UK and international candidates.
Its partner institutions are Swansea University (lead institution), Aberystwyth University, Bangor University, University of Bristol and Cardiff University.
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. Training will be delivered via cohort activities across the partner institutions.
Positions are funded for 4 years, including 6-month placements with the external partners.
AIMLAC CDT Project titles:
- RS191 – AIMLAC1 – Using Machine Learning to understand Lattice QCD Data (Physics)
- RS192 – AIMLAC2 – Optimising Attack-Defence Trees using Evolutionary Computing (Computer Science)
- RS193 – AIMLAC3 – Tests of the dark sector with gravitational waves (Physics)
- RS194 – AIMLAC4 – Data Lab Cymru (Medicine)
- RS195 – AIMLAC5 – AI based approaches multi-dimensional functional genomics in cancer patients (Medicine)
- RS196 – AIMLAC6 – Protein Structure Prediction via Deep Learning Protein Structure Prediction via Deep Learning (Computer Science and Biomedical Science)
- RS197 -AIMLAC7 – Development of a plasma lens for Laser hybrid Accelerator for Radiobiological Applications with an advanced computational approach (Physic and Medical Physics)
Description of research projects and more information can be found at the UKRI CDT in Artificial Intelligence, Machine Learning & Advanced Computing (AIMLAC) website.
- The value of this scholarship is £6,000 and is awarded as a tuition fee waiver. No direct payment is made to any applicant.
- The scholarship is paid in each year of applicable study: a. Undergraduate applicants can receive the scholarship for up to 5 years of progressing study. (£30,000 over 5 years). b. Where the course is a 3.5-year Undergraduate Degree (School of Business) then the scholarship will only be applied in Year 2 onwards. c. Postgraduate Taught applicants (including Master of Research and Masters by Research) – where the course spans more than 12 months full time, and a full year tuition fee is due in each academic year, then the scholarship can be applied in both years of study.
- Scholarships are awarded on an Unconditional basis. However, this is not linked to the Course application status.
- Scholarships cannot be awarded on a pro-rata basis.
The scholarships cover the full cost of tuition fees and an annual stipend of £17,668.
Additional funds will be available for research expenses.
Please visit our website for more information.