We are looking for an advanced quantitative researcher with a background in health data science, health informatics or population health analytics and with demonstrable expertise in applied statistical modelling and causal inference using large-scale administrative health or population datasets. The ideal candidate will have a passion to use their skills and data to produce evidence to improve population health and reduce health inequalities.

This post is for a new NIHR funded project to understand the impact and cost effectiveness of integrated primary care for people experiencing homelessness. You will be a core member of a team that brings together partners from academia, the NHS, local authority and the voluntary sector. The project will use linked data to better understand the needs and service use of people experiencing homelessness. It will evaluate the impact of a dedicated primary care service in Liverpool using causal inference and economic evaluation. The insights of the evaluation will inform new toolkits to design better interventions that are more proportionate to need and more proactive in supporting one of the most vulnerable portions of our society.

You will be part of the Health Inequality Policy Research (HIP-R) Theme in the Department of Public Health, Policy and Systems and a member of the Data Action Research Team (DART) within the theme, cross-cutting with the University of Liverpool Civic Health Innovation Lab (CHIL). This project sits within the portfolio of the Population Health and Prevention Theme of NIHR Applied Research Collaboration North West Coast (ARC NWC). As such, the researcher will be immersed in and contribute to the purpose of a large multi- and interdisciplinary community of researchers and health and care stakeholders which spans several research infrastructures.

You should have a PhD (or equivalent experience) in a quantitative discipline such as Data Science, Statistics, Epidemiology or Health Informatics. This is an exciting opportunity to apply and develop skills in epidemiological studies, causal inference and natural policy experiments and to contribute to high-impact research to inform policy and improve health outcomes, while developing your career in a world-leading public health institute.

This post is fixed term until 30 November 2028.