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Research Assistant in Epidemiology and Health Data Sciences

Job in Oxford, Oxfordshire, OX1, England, UK
Listing for: University of Oxford
Full Time position
Listed on 2026-05-28
Job specializations:
  • Research/Development
    Research Scientist, Clinical Research, Medical Science, Data Scientist
  • Healthcare
    Clinical Research, Medical Science, Data Scientist
Salary/Wage Range or Industry Benchmark: 60000 - 80000 GBP Yearly GBP 60000.00 80000.00 YEAR
Job Description & How to Apply Below

Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Botnar Research Centre, Windmill Road, Oxford, OX3 7LD

We have an exciting opportunity for a Research Assistant in Epidemiology and Health Data Sciences to join the Pharmaco- and Device epidemiology research group led by Professor Daniel Prieto-Alhambra at the Botnar Research Centre, NDORMS, University of Oxford. The NDORMS Pharmaco- and Device epidemiology research group is involved in a number of national and international studies exploring the conditions of use (adherence, compliance, off and on-label use) of a number of licensed drugs, devices, and vaccines for the prevention and treatment of human disease in 'real world' (routine practice) conditions.

  • As a Research Assistant in Epidemiology and Health Data Sciences you will support the analysis and management for studies on our portfolio using routinely collected data mapped to the OMOP Common Data Model.
  • You will contribute to the development of study documentation for our studies, you will use R packages to run a number of pre-specified analyses and you will conduct and support research activities based on your relevant expertise area.
  • You will contribute to publications, scientific reports and journal articles as well as the presentation of data/papers at conferences and other scientific meetings.
  • You will hold a relevant post-graduate degree in Epidemiology or a related field together with experience in biostatistics and/or health data sciences.
  • Experience in programming statistical analyses, preferably in R and experience in writing scientific documents, e.g. study reports, manuscripts are essential.
  • As are ability to work within multi-disciplinary teams and independently, good communication skills and excellent team working skills.
  • Experience in the analysis or interpretation of OMOP-mapped data, experience in working with electronic medical records/routinely collected/real world data and experience in generating phenotypes are desirable.

This is a full-time fixed-term appointment for 2 years.

The closing date for this position is 12 noon on 10 May 2024. You will be required to upload a CV and supporting statement as part of your online application.

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