Purpose of the post
This is an exciting opportunity to take on a national leadership role to work with the BHF Data Science Centre on a part-time secondment basis. The Computable Cardiovascular Phenotypes Theme Lead will be a key member of the BHF Data Science Centre leadership team, taking on an Associate Director role. They will work closely with the Director, other Associate Directors and centre staff to identify and prioritise key areas of work in the development, refinement and use of phenotyping algorithms for cardiovascular research with impact at national and international level. They will have an excellent understanding of, and expertise in, the development and use of computable phenotypes (from simple code lists through more complex methods that combine structured and unstructured data sources) in health research, and a strong commitment to open science and sharing of tools and approaches to further the understanding of causes, prediction, progression and management of cardiovascular disease.
Supported by the BHF Data Science Centre team, the postholder will work with stakeholders across the UK to:
- identify priority research questions for development and use of computable cardiovascular phenotypes;
- identify where developing and refining algorithms to define and standardise cardiovascular phenotypes and sub-phenotypes are required;
- work closely with Associate Directors from other thematic areas to drive development of computable phenotypes across a wide range of health data (including from electronic health records, hospital record data, imaging and free text), identifying and linking new data sources where appropriate.
- identify and address the infrastructure and data-driven analytics challenges that need to be overcome to ensure that robust and reproducible computable phenotypes from large-scale health data can be developed and validated to inform the causes, prediction, progression, prevention and treatment of cardiovascular diseases.
There will be overlap with the centre’s other thematic areas and collaborative working with other leads across these themes is expected. Collaboration with HDR UK’s ‘Human Phenome’ project and the HDR UK CALIBER Phenotype Library will be essential. Close working with HDR UK’s Data Improvement Team is also expected, for example on data utility, data standards and synthetic data.
This part-time role would provide leadership and strategic planning in the development and use of computable phenotypes for cardiovascular research, to meet the wider objectives of the BHF Data Science Centre in improving cardiovascular health through the use of large-scale data and innovative analytical methods.
This post would suit a health data scientist (either clinical or non-clinical) with expertise in developing and validating computable phenotype algorithms, who is an established leader or well advanced on a career pathway towards a leadership position within this field.
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