Swansea University’s UKRI CDT Artificial Intelligence, Machine Learning, and Advance Computing is fully funded.
Swansea University offers three fully funded PhD scholarships under this competitive scholarship scheme.
AIMLAC (Artificial Intelligence, Machine Learning, and Advance Computing) aims to train the next generation of AI innovators in a variety of STEMM disciplines. The CDT offers advanced multidisciplinary training in an inclusive, caring, and open environment that encourages each student to reach their full potential. Applications from candidates with diverse backgrounds who can positively contribute to our society’s future are encouraged.
The fully-funded scholarships from UK Research and Innovation (UKRI) cover the full cost of tuition, a UKRI standard stipend of £17,668 per year, and additional funding for training, research, and conference expenses.
The scholarships are available to both UK and international applicants.
Swansea University (the lead institution), Aberystwyth University, Bangor University, the University of Bristol, and Cardiff University are its partners.
AI training, high-performance computing (HPC), and high-performance data analytics (HPDA) are critical, as is collaboration with external partners, which include large international corporations, locally based start-ups and SMEs, as well as government and Research Council partners. Cohort activities will be used to deliver training 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.
Please see individual project adverts for more information on eligibility.
This scholarship is open to candidates of any nationality.
NB: If you are holding a non-UK degree, please see Swansea University degree comparisons to find out if you meet the eligibility.
If you have any questions regarding your academic or fee eligibility based on the above, please email firstname.lastname@example.org with the web-link to the scholarship(s) you are interested in.
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.