Oxford Population Health (Nuffield Department of Population Health, University of Oxford), Old Road Campus, Headington, Oxford
Nuffield Department of Population Health, Old Road Campus, Headington, Oxford, Grade 7
We are seeking a well-organised individual with a strong interest in programming, data analyses, and quality control. The health data analyst will be part of a team of approximately 10 individuals at Oxford, including DPhils, postdocs, and administrators. The Oxford team works across statistical, machine learning, and image analysis methods. The primary focus of this role is to manage the unique, highly dimensional data (spatial-temporal, images, biomedical datasets, etc.) generated from the cohort in Uganda. This post provides an exciting opportunity to work with diverse data types, address a disease of poverty, and join a multi-disciplinary team employing quantitative approaches to novel biomedical problems. The position is a great opportunity for someone with a quantitative background, who would like to gain experience working with a large research team on challenging data science projects.
The post is suitable for someone with excellent programming and statistical analysis skills from a quantitative background who has an interest in infectious disease research. The candidate will report directly to the study PI, Professor Goylette Chami.
Applications for this vacancy are to be made online and require a supporting statement and CV. The supporting statement must address the selection criteria for the post using examples of your skills and experience. Informal enquires are encouraged and should be addressed to Prof. Goylette Chami (Goylette.chami@ndph.ox.ac.uk). Further particulars, including details of how to apply, can be obtained from the document below.
Applications for this vacancy should be made online and you will be required to upload a CV and supporting statement as part of your application. Only applications received by 12.00 midday on 23rd November 2026 will be considered.
Tagged as: Life Sciences
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