What is a Biomedical Data Scientist?
A Biomedical Data Scientist is a broad term defined by UKRI to encompass the many roles that in biomedical research that require computational, mathematical and statistical expertise.
We define biomedical data scientists as someone who applies computational, mathematical or statistical skills in a biomedical research field this includes (and is not limited to) all researchers, educators, data stewards, research infrastructure or software engineers contributing or enabling biological, medical or health research that improves our understanding of health and disease.
This includes (and is not limited to) those working in: ‘omics’, software engineering, mathematical modelling, statistics, machine learning and AI, image analysis, population health data, clinical trials, medical devices, wearable technology, computational biology, research computing infrastructure and support or training of data science skills.
We want to hear views and involve as many of the community as possible. We welcome anyone who uses programming, mathematical and statistical skills to call themselves a biomedical data scientist whether they are performing research themselves or enabling the infrastructure that allows researchers to flourish.
Our Plans
Over the course of the project we aim to pilot and evaluate initiatives designed to encourage, support and reward data scientists, to drive better collaboration across UK biomedical science and embed a supportive and sustainable culture that fully includes all data scientists.
Our Activities
- Virtual inspiration board of case studies that support career development, mobility and embed collaborative interdisciplinary working.
- Evidence-based report for funders and research institutes to highlight successful models to support biomedical data scientiststhat meetneeds of researchers and industry partners to maximisebenefit to all parties. Identification of concerns and challenges for adoption.
- Code of conduct templates for expected behaviors, recognition and career development outcomes for collaborative projects –Lab Handbook model
- Report on considerations, incentives and mechanisms for implementing secondment opportunities with industry and other labs.
- Online Careers workshop and talks to support professionalskills development of biomedical data scientists –communication, networking etc.
We are currently in the process of launching a survey to map examples of good practices that have supported data scientists in their career and personal development. To keep informed of the launch please sign up to our mailing list here: INTEGRATE-BIO@jiscmail.ac.uk
