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Details of Grant 

EPSRC Reference: EP/Y030974/1
Title: UKRI AI Centre for Doctoral Training in Digital Healthcare
Principal Investigator: Faisal, Professor A
Other Investigators:
Quint, Professor J Bharath, Professor AA Ashby, Professor D
Rei, Dr M Parbhoo, Dr S Darzi, Professor AW
Barahona, Professor M Levy, Professor JB Haddadi, Professor H
Researcher Co-Investigators:
Project Partners:
ARCHIMEDES Avado Learning Limited British Standards Institution BSI
Delta Biosciences Dynamic Metrics Ltd Faculty of Clinical Informatics
GripAble Hocoma Imperial College Health Partners
Institution of Engineering & Technology Intersystems Jiva AI Ltd
Koa Health Lenus Health Loft Digital Limited
MasterCard Europe Services Ltd Medical Research Council (MRC) Metalynx Ltd
Mettle Mountain Genomics Nat Inst for Health & Care Excel (NICE)
NIHR Imperial Biomedical Research Centre Nokia Nolea Health LtD
Nuance Communications nVIDIA Proxximos Limited
SAIL Databank Scale Space Scan Computers
Serg Technologies Siemens Skin Analytics Ltd
Square ML Syndesis Health Technical University of Munich
The Future Care (UK) Ltd Tutti Toot Ltd UK BioIndustry Association (BIA)
Ultromics Ltd Unhindr Vesynta Ltd
Department: Computing
Organisation: Imperial College London
Scheme: Centre for Doctoral Training
Starts: 01 October 2024 Ends: 31 March 2033 Value (£): 9,286,672
EPSRC Research Topic Classifications:
Artificial Intelligence Biomedical sciences
Drug Formulation & Delivery Med.Instrument.Device& Equip.
Medical science & disease
EPSRC Industrial Sector Classifications:
Healthcare
Related Grants:
Panel History:
Panel DatePanel NameOutcome
06 Sep 2023 UKRI CDTs in Artificial Intelligence 2023 expert panel Announced
20 Sep 2023 UKRI CDTs in Artificial Intelligence Interview Panel E Announced
Summary on Grant Application Form
The UKRI AI CDT in Digital Healthcare (DigitalHealth CDT) will build on our established track record of research training to create a world-leading centre for PhD training of the next-generation innovators in AI applied to Digital Healthcare. Using AI in healthcare will provide more accurate medical decisions faster while reducing suffering, waiting times and costs across society, helping to address the pressing unmet health & care needs. AI for digital healthcare contains all the challenges that make AI generally a hard problem, yet to apply AI to healthcare effectively, we cannot use off-the-shelf AI but have to develop methods that are patient-ready and which address the challenges particular to the ethical, legal and regulatory requirements for healthcare. For example, the NHS requires 10,000 data & AI experts over the next five years as part of their recruitment strategy. Thus there is a pressing need for patient-ready AI specialists that can apply their skills, lead efforts and multidisciplinary teams in this heavily regulated domain. To address this need, our CDT and industrial and NHS partners propose training 121 PhD students including clinicians and allied NHS healthcare professions in five cohorts of 24+ students. Our PhD student journey is structured into multiple phases; in the first year-long phase, students will start their research and learn the technical aspects of AI and their specific application to healthcare. We broaden their training bespoke CDT advanced courses and hands-on training that only make sense for vast research cohorts such as ours to introduce them to the complex healthcare sector. These offerings, the academic and technical scope, comprise studies in AI ethics, healthcare practice and regulation, as well as hands-on software carpentry for vast NHS primary care (SAIL) and hospital databases (London SDE), as well as biobanking (UK BioBank) know-how on the technical end such as deep learning, federated machine learning and foundation models. Including these training aspects are key due to the immediate impact that our NHS and industry-aligned projects in the AI in Digital Health Centre for doctoral training can have on the life and health of citizens. Core to our approach is thus not only bespoke cohort-based training but also cohort-lead activities, such as funds for regular international speakers, seminars, hackathons and work-social events, as well as co-location that will keep these cohorts engaged and developing together. Therefore, our cohorts will endeavour to offer a rich mix of students from mathematics, computer science, engineering, physics, physiology, psychology, medical, and non-clinical professionals such as therapists and pharmacists. Our training offering is enhanced through co-created content by our industry partners that can help catalyse spin-offs (Scalespace), regulatory training (MHRA, HRA, BSI), data access (SAIL, LondonSDE, UK Biobank), as well as NHS trusts. Our graduating PhDs research will represent a new generation of diverse AI researchers with backgrounds ranging from computer science to design engineering and clinical medicine that can develop and deploy AI seamlessly across disciplinary boundaries to deliver health and care. We have teamed up with 3 NHS Trusts and clinical institutions to enable direct clinical involvement and impact - promoting on-site research & development of our students' projects and more than doubled the total number of UKRI studentships with studentships contributed by the UK's vibrant Digital Health industry and institutions. Our focus on AI for Digital Healthcare is not only addressing a pressing need but has also been recognised by our 44 partners and institution, which enabled us to multiple the requested UKRI investment three times (3X), evidence of the importance of this CDT.

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