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Details of Grant 

EPSRC Reference: EP/S02428X/1
Title: EPSRC Centre for Doctoral Training in Health Data Science
Principal Investigator: Davies, Professor J
Other Investigators:
Rittscher, Professor J Nichols, Professor T Hallowell, Professor N
Researcher Co-Investigators:
Project Partners:
Celgene Research Elsevier (International) GlaxoSmithKline plc (GSK)
IBM UK Ltd Insilico Medicine McLaren Applied Technologies
MedaPhor Ltd Microsoft nVIDIA
Oxford Uni. Hosps. NHS Foundation Trust Perspectum Diagnostics Sensyne Health
UCB Vertex Pharmaceuticals Zegami
Department: Computer Science
Organisation: University of Oxford
Scheme: Centre for Doctoral Training
Starts: 01 April 2019 Ends: 30 September 2027 Value (£): 6,944,366
EPSRC Research Topic Classifications:
Artificial Intelligence Image & Vision Computing
Information & Knowledge Mgmt
EPSRC Industrial Sector Classifications:
Healthcare Pharmaceuticals and Biotechnology
Related Grants:
Panel History:
Panel DatePanel NameOutcome
07 Nov 2018 EPSRC Centres for Doctoral Training Interview Panel C – November 2018 Announced
Summary on Grant Application Form
Data science and artificial intelligence will transform the way in which we live and work, creating new opportunities and challenges to which we must respond. Some of the greatest opportunities lie in the field of human health, where data science can help us to predict and diagnose disease, determine the effectiveness of existing treatments, and improve the quality and affordability of care.

The Oxford EPSRC CDT in Health Data Science will provide training in:

- core data science principles and techniques, drawing upon expertise in computer science, statistics, and engineering

- the interpretation and analysis of different kinds of health data, drawing upon expertise in genomics, imaging, and sensors

- the methodology and practice of health data research, drawing upon expertise in population health, epidemiology, and research ethics

The training will be provided by academics from five university departments, working together to provide a coordinated programme of collaborative learning, practical experience, and research supervision.

The CDT will be based in the Oxford Big Data Institute (BDI), a hub for multi-disciplinary research at the heart of the University's medical campus. A large area on the lower ground floor of the BDI building will be allocated to the CDT. This area will be refurbished to provide study space for the students, and dedicated teaching space for classes, workshops, group exercises, and presentations.

Oxford University Hospitals NHS Foundation Trust (OUH), one of the largest teaching hospitals in the UK, will provide access to real-world clinical and laboratory data for training and research purposes. OUH will provide also access to expertise in clinical informatics and data governance, from a practical NHS perspective. This will help students to develop a deep understanding of health data and the mechanisms of healthcare delivery.

Industrial partners - healthcare technology and pharmaceutical companies - will contribute to the training in other ways: helping to develop research proposals; participating in data challenges and workshops; and offering placements and internships. This will help students to develop a deep understanding of how scientific research can be translated into business innovation and value.

The Ethox Centre, also based within the BDI building, will provide training in research ethics at every stage of the programme, and the EPSRC ORBIT team will provide training in responsible research and innovation. Ethics and research responsibility are central to health data science, and the CDT will aim to play a leading role in developing and demonstrating ethical, responsible research practices.

The CDT will work closely with national initiatives in data science and health data research, including the ATI and HDR UK. Through these initiatives, students will be able to interact with researchers from a wide network of collaborating organisations, including students from other CDTs. There will also be opportunities for student exchanges with international partners, including the Berlin Big Data Centre.

Students graduating from the CDT will be able to understand and explore complex health datasets, helping others to ask questions of the data, and to interpret the results. They will be able to develop the new algorithms, methods, and tools that are required. They will be able to create explanatory and predictive models for disease, helping to inform treatment decisions and health policy.

The emphasis upon 'team science' and multi-disciplinary working will help to ensure that our students have a lasting, positive impact beyond their own work, delivering value for the organisations that they join and for the whole health data science community.

Key Findings
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Potential use in non-academic contexts
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Date Materialised
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Project URL:  
Further Information:  
Organisation Website: http://www.ox.ac.uk