Health data in practice: human-centred science

Our Wellcome-funded doctoral training programme applies human-centred data research to health and care data, and will introduce you to a wider context for your research, enabling you to draw on concepts, disciplines and methods underpinning algorithmic designs, sensing and data capture, human-interactions, qualitative and quantitative evaluation and decision-making, in real-world settings. You will develop as a future scientific leader able to apply interdisciplinary perspectives to your research and realise the potential of innovations in health data research for the benefit of patients, the public, health care systems, and society.

The Wellcome Trust Health Data in Practice programme combines scientific excellence with a commitment to improving the working environment and transition support for trainees. We commit to being part of an evolving community of practitioners who will develop and share practice to bring science and culture together, placing both firmly at the heart of what we do.

The availability, scale and depth of data collected in the course of health care, by or about patients – combined with data-driven approaches to its analysis – is creating a paradigm shift in health care and its delivery. Machine learning and other automated methods of analysis will only succeed in providing useful insights for health and care if we understand health data in practice: how data is actually generated, interpreted and used.

Human-centred data science operates ‘at the intersection of human-computer interaction, computer-supported cooperative work, human computation, and statistical and computational techniques of data science’ while preserving ‘the richness associated with traditional methods while utilising the power of large data sets.’ We adapt this concept to the 'health data in practice' doctoral training programme with the goal of developing highly skilled future leaders able to apply interdisciplinary perspectives to research and innovations in health data science for the benefit of patients, the public, health care systems and society.

You must be a graduate or student who has, or expects to obtain, at least an upper second-class degree (or equivalent for EU and overseas candidates) in a relevant subject. Relevant subjects include quantitative disciplines such as Statistics, Computer Sciences, Mathematics, Bioinformatics and Biomedical Sciences, and qualitative disciplines such as Anthropology, Ethnography and Social Sciences.

Candidates with other relevant qualifications or research experience may also be eligible. Please not that medical, dental or nursing undergraduate degrees are not considered relevant disciplinary areas.