Research Fellow in Epidemiology/Health Data Science

About us

UCL established the Institute of Health Informatics (IHI) in August 2014 in the Faculty of Population Health Sciences. The aim of IHI is to conduct high quality data-intensive research to improve health at local, national, and international levels.

The Faculty of Population Health Sciences has established itself as UCL’s largest research-based faculty, encompassing eight institutes. More information available at www.ucl.ac.uk/population-health-sciences/.

About the role

Institute of Health Informatics is looking to appoint a full time (36.5 hours per week) Research Fellow in Epidemiology / Health Data Science to join our welcoming and vibrant Institute.

This position presents a unique opportunity to join a team of experienced health data scientists, informaticians, statisticians and clinical epidemiologists and contribute significantly to the statistical analysis and subsequent presentation of results from large scale national and rich local health record data resources. The Research Fellow in Epidemiology / Health Data Science will analyse health data from 56 million people including coded data in Hospital Episode Statistics from the NHS England Secure Data Environment and primary care. They will develop reproducible analytic pipelines in one or more of the following: health care procedure data, geographic location data and/or temporal trends, and will design and execute analytic pipelines in our Atlas for Health.

A full range of duties can be found on the attached job description.

The post is funded until 31 December 2026, further funding may become available.

For an informal discussion please contact Professor Harry Hemingway at h.hemingway@ucl.ac.uk .

About you

The Research Fellow in Epidemiology / Health Data Science must have a PhD or appropriate equivalent experience in epidemiology, data science, biostatistics or related quantitative discipline as well excellent statistical analysis programming skills in R and/or R-Studio and the ability to meet deadlines and work effectively as part of an inter-disciplinary team. The role holder will have experience of wrangling large-scale, structured electronic health records and experience using disease ontologies and classifications (particularly International Classification of Didsease-10th revision), and experience developing reusable pipelines for managing and analysing large datasets (>100 million rows).

Please review the job description before applying, paying particular attention to the essential / desirable criteria, and ensure your experience in these areas is addressed in the questionnaire section of the application.

What we offer

As well as the exciting opportunities this role presents, we also offer some great benefits visit https://www.ucl.ac.uk/work-at-ucl/reward-and-benefits to find out more.

Our commitment to Equality, Diversity and Inclusion

As London’s Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world’s talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong.

You can read more about our commitment to Equality, Diversity and Inclusion here https://www.ucl.ac.uk/equality-diversity-inclusion/

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