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The role
This is an exciting opportunity to join a UKRI-funded fellowship project modelling how health and care needs change across England's diverse neighbourhoods as the population ages. You'll work closely with the Fellow (Dr Richard Green) during a focused period at the heart of the project's analytical work. This is a part-time (0.5 FTE) fixed-term contract until January 2027.
You Will
- Support the development of multilevel longitudinal models estimating health transition probabilities (e.g. functional decline, multimorbidity, care dependency) using linked ELSA and neighbourhood-level data
- Contribute to integrating these models into the English Future Elderly Model (E-FEM)
- Help translate modelling outputs into clear visualisations and summaries for policy and practice audiences, including NHS Integrated Care Boards and local authorities
- Work within the UK Data Service's secure research environment, applying rigorous approaches to data management and disclosure control
- Contribute to the preparation of policy briefs and support the planning of stakeholder workshops towards the end of the project
This is a hands-on research role suited to someone who wants to build applied experience in longitudinal and simulation modelling, working on a project with direct relevance to national health and social care policy.
About You
You will have:
- A postgraduate qualification (or equivalent research experience) in statistics, data science, or a related quantitative discipline
- Demonstrable experience conducting statistical or longitudinal data analysis using R (or a similar statistical programming language)
- The ability to work independently on technical tasks while communicating findings clearly to a non-specialist audience
Research Fellow in Health Sciences in Guildford employer: University of Surrey
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