Various Subject Areas: Fully Funded UKRI CDT Artificial Intelligence, Machine Learning and Advance Computing (AIMLAC) PhD Scholarships 2022
Closing date: 11 February 2022
Funding provider: UK Research and Innovation (UKRI)
Subject areas: Biological and Health Sciences; Mathematics and Computer Science; Physics and Astronomy
Project start date: 1 October 2022 (Enrolment open from mid-September)
Aligned programme of study: PhD
Mode of study: Full-time only
This is a competitive scholarship scheme and two 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 £15,921 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.
The partners include: We Predict, ATOS, DSTL, Mobileum, GCHQ, EDF, Amplyfi, DiRAC, Agxio, STFC, NVIDIA, Oracle, QinetiQ, Intel, IBM, Microsoft, Quantum Foundry, Dwr Cymru, TWI and many more.
AIMLAC CDT Project titles
- RS20-AIMLAC01 - Topological excitations and colour confinement in gauge theories (Mathematics)
- RS21-AIMLAC02 - Multimodal analysis of Anatomical and Functional features to enhance the understanding of Brain Processing Phenomena: A Machine Learning Approach (Computer Science)
- RS22-AIMLAC03 - Ultrafast pulse shaping via machine-learning-enabled multi-element adaptive optics and levitated optomechanics (Physics)
- RS23-AIMLAC04 - Multi-view data integration to predict nanomedicine efficacy; driving the future reality? (Medicine)
- RS24-AIMLAC05 - Analogue Computing for Advanced Machine Learning and Sensing (Physics)
- RS25-AIMLAC06 - Learning (from) lattice field theory (Physics)
- RS26-AIMLAC07 - Visual Analytics for Public Health Network Analysis (Computer Science)
- RS27-AIMLAC08 - Robust Parameter Optimisation for Image Segmentation (Computer Science)
Description of research projects and more information can be found at the UKRI CDT in Artificial Intelligence, Machine Learning & Advanced Computing (AIMLAC) website.
Please click on the link for the project you are interested and complete the APPLY online form. Please quote the project code (e.g. RS20-AIMLAC01) for queries and within the application. If you wish to apply for more than one project, please add the code and project title within the text and you will be considered for all projects.
Candidates must normally hold an undergraduate degree at 2.1 level in a related discipline, or an appropriate master’s degree with a minimum overall grade at ‘Merit’ (or Non-UK equivalent as defined by Swansea University). See - Country-specific Information for European Applicants and Country-specific Information for International Applicants.
English Language requirements: If applicable – IELTS 6.5 Overall (with no individual component below 6.0 or 6.5) or Swansea University recognised equivalent. Full details of our English Language policy, including certificate time validity, can be found on our website.
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 email@example.com 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 £15,921.
Additional funds will be available for research expenses.
How to Apply
To apply, please visit the individual scholarship advert page.
For enquiries, please contact Rhian Melita Morris and Roz Toft (firstname.lastname@example.org).