Research Fellow (2 posts) Unit for Lifelong Health and Ageing at UCL (LHA)

The Unit for Lifelong Health and Ageing at UCL (LHA) is seeking to appoint two full-time Research Fellows to work on projects addressing the causal relationship between work, employment and health. The mission of LHA is to identify biological and social factors that affect lifelong health, ageing and the development of chronic disease, and to use findings to inform policy and design and test interventions that enhance healthy ageing.

These positions will suit researchers with a strong interest in the causal relationships between work, employment, and different aspects of health. The successful applicants will lead on the analysis of quantitative data from a range of data sources and disciplines, conduct original research leading to publication, and will be supported in developing an independent research career.

Position 1 (3-year Research Fellow): This post will contribute to two projects led by Professor Praveetha Patalay and Dr Jacques Wels. Approximately one third of the role will be dedicated to research on the health determinants of young people Not in Employment, Education or Training (NEET) in the UK. The remaining two thirds will focus on the UKRI-funded UHealth project, which investigates the impact of trade unions on workers’ health using longitudinal datasets such as Understanding Society, the Millennium Cohort or Next Steps, as well as international longitudinal datasets.

Position 2 (2-year Research Fellow): This post will focus on the UKRI-funded UHealth project, led by Dr Jacques Wels, addressing two main work packages: (1) the longitudinal trajectories of workers and the potential protective effects of trade union presence and membership on health outcomes across the lifecourse; (2) a cross-country comparison of the relationship between trade unions and workers’ health using longitudinal data.

Applicants should hold a PhD in social epidemiology, data science, health informatics, biostatistics, or the social sciences, including sociology or psychology. They should have experience of working with longitudinal and population-based health datasets, and strong quantitative skills in longitudinal analysis, including causal inference methods and multiple imputation. Experience in using R or Stata is required, and an interest in cross-country comparative analyses would be advantageous. Candidates must be able to demonstrate evidence of conducting quantitative analysis and research leading to outputs of publishable standard.