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Data Scientist Assistant

University of Oxford - Oxford Vaccine Group, Centre for Clinical Vaccinology and Tropical Medicine / Institute of Developmental and Regenerative Medicine

Location: Oxford
Salary: £35,681 to £41,636 per annum (with a discretionary range to £45,212 per annum): Grade 6
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 16th July 2026
Closes: 31st July 2026
Job Ref: 187623

About the role

We have an exciting opportunity for a highly motivated Data Scientist Assistant to join the Oxford Vaccine Group (OVG) as part of the Correlates of Immunity – Artificial Intelligence (CoI-AI) Programme, a pioneering initiative that integrates controlled human infection models, advanced immunology, and AI-driven analytics to accelerate vaccine discovery.

The postholder will contribute to the data science and computational workstream of the programme, supporting the analysis and integration of complex datasets generated from vaccination studies, natural infection studies, and controlled human infection models. The role will focus on the processing, management, statistical analysis, and visualisation of immunological, clinical, and microbiological data to enable robust downstream interpretation and AI-driven discovery.

Working within a multidisciplinary team of data scientists, computational biologists, immunologists, and microbiologists, the postholder will develop, maintain, and optimise reproducible data analysis pipelines and databases. The role includes contributing to study planning, data interpretation, and reporting, ensuring analytical outputs are robust, harmonised, and suitable for publication and dissemination.

The Data Scientist Assistant will support day-to-day computational activities within OVG, including workflow development using systems such as Snakemake and Nextflow, bioinformatic and statistical analyses, and the maintenance of clinical trial databases. The postholder will be expected to use version control and collaborative code management platforms (e.g. Git/GitHub) as standard practice for developing reproducible and maintainable analytical workflows. The role requires a self-motivated and well organised individual who can communicate effectively with the line manager and wider team to support programme objectives.

You will be working in a growing department within the Medical Sciences Division. The Department of Paediatrics is a world leader in child health research and hosts internationally renowned research programmes in drug development, gastroenterology, haematology, HIV, immunology, neuroimaging, neuromuscular diseases and vaccinology. The Oxford Vaccine Group is a world-leading academic research group conducting clinical and translational studies to advance vaccine development working with a diverse portfolio funded by industry, government and charitable organisations.

This position is offered full-time on a fixed-term contract initially for 2 years with the possibility to extend provided further external funding is available.

About the department 

Please visit our website to find out more about the Department.

About you

You will hold a degree (or be near completion of a higher degree) in Data Science, Statistics, Computing, Bioinformatics, Life Sciences, or a closely related discipline, with sufficient technical knowledge to contribute effectively to an established research programme. You will have demonstrable experience working with complex biological, clinical, or health-related datasets and applying statistical or computational methods to support research questions.

You will be able to manage your own analytical tasks, deliver high-quality outputs to agreed deadlines, and communicate results clearly through written reports, figures, presentations, and contributions to publications. You will have a collaborative approach, with the ability to work effectively within multidisciplinary teams spanning data science, immunology, microbiology, and computational research, and the willingness to develop new skills as required by the programme.

Only online applications received before 12.00 midday on 31 July 2026 will be considered. Interviews will be held as soon as possible thereafter.

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