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Apply now: call for research proposals in cardiovascular data science

The British Heart Foundation and The Alan Turing Institute have launched a joint funding call aimed at generating data science solutions to key cardiovascular problems.

Proposals are invited from multi-disciplinary teams for small (≤£50,000) or medium scale (£50,000-£150,000) projects which demonstrate collaboration between one or more data scientists and cardiovascular investigators. Proposals should be co-led by a cardiovascular researcher, with an appointment at a UK academic institution, and a data scientist, who must be directly associated with The Alan Turing Institute or its founding university partners.

Proposals must be innovative in nature, utilise existing data and clearly explain the potential impacts of the work for cardiovascular research and data science. The research undertaken may include foundational research (where the aim is to generate new knowledge and understanding in cardiovascular science) or focus on translational application.

Applications will be assessed by a multidisciplinary panel co-chaired by Professor Neil Lawrence (Director of Machine Learning at Amazon Research Cambridge and Professor of Machine Learning at the University of Sheffield) and Professor Andrew Morris (Director of Health Data Research UK and Professor of Medicine and Vice-Principal Data Science at the University at Edinburgh).

The call was generated following  a Turing-BHF scoping workshop held in March 2017 which identified a range of interesting opportunities where cardiovascular research would benefit from data science tools and techniques, such as data access, privacy and anonymization, machine learning, image analysis, modelling and technical infrastructure. Read more in the call announcement.

Application process and contact

If you are a cardiovascular researcher that would like to collaborate with a Turing-based data scientist, please contact Dr Mahlet Zimeta, Programme Manager at mzimeta@turing.ac.uk .

The closing date for proposals is 09:00 GMT on 16 October 2017.

Further details and how to apply.