The Alan Turing Institute (the Turing) and the British Heart Foundation (BHF) invite proposals from multidisciplinary teams of researchers working in partnership to apply data science approaches to challenges faced in cardiovascular research.


Cardiovascular disease kills around one in four people in the UK, taking the lives of more than 100 people under 75 every day, and affects the daily life of 7 million people. Modern data science offers new ways of gaining valuable insight into the aetiology and treatment of cardiovascular disease, towards ending the devastation that it causes.

Over recent years we have experienced a transition into an era of digital medicine, typified by advances in technology and an exponential increase in the generation of new datasets, many of which are characterised by their volume, variety, and complexity. Such datasets include, but are not limited to, molecular data generated by ‘omics technologies, medical imaging data and health data derived from patient records. The application of data science approaches and innovative analyses of these datasets have the exciting potential to improve the diagnosis, treatment, and prognosis of patients across medical disciplines. Conscious that responsible medical research requires patient privacy and anonymity are upheld, data science innovations around privacy and anonymisation are also an important contribution to this field.


This joint call between the BHF and the Turing aims to catalyse productive collaborations between cardiovascular investigators and specialist data scientists. It is designed to enable groups of researchers with complementary skills and expertise to explore opportunities at the nexus of cardiovascular research and data science research.

Proposals are invited from multi-disciplinary teams for small (≤£50,000) or medium scale (£50,000-£150,000) projects with a demonstrable synergy between data scientist(s) and cardiovascular investigator(s). Proposals must be innovative in nature, utilise existing data (that is fully consented and anonymised) and clearly explain the potential impacts of the work for cardiovascular 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. While applicants may seek to address or contribute to the addressing of any cardiovascular challenge(s) that would benefit from data science approaches, a recent joint workshop identified the following areas as particularly important:

    • Data access
    • Privacy and anonymisation
    • Machine learning
    • Image analysis
    • Modelling, and in particular statistical modelling
    • Exploitation of advanced computing technologies


All proposals must be co-led by one cardiovascular investigator and one data scientist. At least one of the PIs must be a senior academic researcher with a strong track record of grant support and research outputs. Projects must start by mid-April 2018.

For the purposes of this call, the following institutional eligibility criteria apply:

Cardiovascular researchers: Lead applicants must hold an appointment at an established UK academic institution with significant cardiovascular research activity. Additional cardiovascular investigators without academic affiliation may participate, but may not lead.

Data scientists: Lead applicants must be either Turing Fellows, Turing Research Fellows or situated at one of the Turing’s founding university partners. Additional scientists who are not directly involved with the Turing or its founding university partners may participate, but may not lead.

The BHF and Turing are actively committed to promoting equality and diversity.

Funding available

Applicants may submit proposals for up to £150,000 direct costs for projects of 6-24 months in duration.

Awards may include:

  • Staff salaries (e.g. existing academic staff, research assistants or other research staff, technicians and other support staff). Please note that PhD studentships cannot be supported through this call.
  • Research consumables directly attributable to the project.
  • Research equipment essential for the project.
  • Travel and subsistence, and other meeting costs where relevant.

How to apply

All applications must be made online via the Turing’s Flexigrant portal. Before applying read the full guidance notes.

Applicants will be required to complete the following sections on the Flexigrant portal directly or as a PDF upload to the portal, as indicated:

  • Lead applicant and co-investigator details
  • CVs
    • Lead applicants (max. 2 pages, .pdf)
    • Other investigators (max. 1 page, .pdf)
  • Relevant publications from the application group (max. 2 pages for all researchers combined and provided as a single .pdf)
  • Scientific abstract and lay summary (max. 200 words each)
  • Research proposal (max. 4 pages, plus an additional page for references if needed, as a single PDF file) that includes:
    • Case for support (including background, aims and objectives, tools and methods, relevance and beneficiaries, dissemination and impact)
    • Workplan (including timeline, milestones and deliverables)
  • Financial details:
    • Directly Allocated (e.g. staff salaries)
    • Directly Incurred (e.g. consumables, equipment)
    • Other costs (e.g. travel & subsistence)
  • Impact statement (max. 200 words)
  • Ethical approval status from applicants’ academic institution and confirmation of consent for data use
  • Letters of support (to show support from applicants’ academic institutions to cover indirect costs and where specific provision of resources is stated in the application, .pdf)

Applications must be submitted no later than 09:00 GMT on 16 October 2017.

Only applications submitted through the Turing’s Flexigrant system will be accepted for processing. The application submitted through Flexigrant will be taken to be the final version, and will be the version used for assessment.


All applications will be assessed by a specially-constituted multidisciplinary panel, chaired by Professor Neil Lawrence and Professor Andrew Morris, against the following criteria:

  • Innovative nature and added value of the proposed work
  • Availability and quality of data
  • Impact of anticipated outcomes
  • Potential added value of combined expertise of co-investigators
  • Value for money

What we will do with your information

In accordance with the Data Protection Act 1998, the personal information that you provide within the application will specifically be used for the purpose of administering this call. The information will be viewed by BHF and Turing staff and selection panel members, and your information will not be used for any other purpose without your specific consent.

Application and award timetable

Opening date for applications4 September 2017

Closing date for applications09:00 on 16 October 2017

Review panel meetingDecember 2017

Project start dateBy mid-April 2018


If you are a cardiovascular researcher that would like to collaborate with a Turing-based data scientist, or if you have questions about the application process or any other aspect of the call, please contact Dr Mahlet Zimeta, Programme Manager ([email protected] ).