At a Glance
- Tasks: Analyse multiomic prostate cancer data to uncover genetic patterns and improve treatment outcomes.
- Company: University of Oxford, a leading institution in research and innovation.
- Benefits: Full-time position with potential for remote work and opportunities for academic publications.
- Other info: Fixed-term contract until December 2027 with excellent career development prospects.
- Why this job: Join a groundbreaking project that aims to revolutionise prostate cancer treatment and patient care.
- Qualifications: PhD/DPhil in relevant fields and strong programming skills, especially in machine learning.
The predicted salary is between 63000 - 77000 £ per year.
Location: Old Road Campus, University of Oxford, OX3 7LF
Contract type: Fixed term until 31st December 2027
Hours: Full-time
About the role
We are seeking a creative and enthusiastic data scientist or bioinformatician to join an exciting project to uncover patterns of genetic alterations associated with treatment susceptibility in prostate cancer. The project is funded by a recent Prostate Cancer UK award to identify translational results in data compiled by the Pan Prostate Cancer Group, a worldwide initiative to bring together multiomic data from sites across the world. The outputs of this project will pave the way for treatments to be targeted to subsets of patients who will benefit the most, leading to improved outcomes for patients while minimising unnecessary treatments and associated side effects. The position will be based at Old Road Campus, Oxford, but you may be able to agree a pattern of regular remote working with your line manager.
About you
Your primary responsibility will be to analyse our expansive multiomic prostate cancer data set and identify features that enable integration with more limited data arising from clinical trials. You will therefore need strong programming and data analysis skills, with proficiency using machine learning methods. You should be willing to learn and apply both bioinformatics and machine learning methods to curate and compare disparate data sets from different sources. You will be comfortable working independently, while also contributing ideas and communicating results to collaborators across the wider research project. You will have completed, or be near completion of, a PhD/DPhil in Mathematics, Statistics, Computer Science, Bioinformatics, Physics, Engineering, or a related discipline. You will have the ability to develop academic publications, evidenced through a track record of contributing to publications and presentations. Previous experience in advanced machine learning approaches for tabular data, familiarity with bioinformatics tools for processing DNA or RNA sequencing outputs, and knowledge of cancer biology, genetics, and evolution would be desirable.
This full-time post is available immediately and is fixed-term until 31st December 2027 in the first instance.
Application Process
If you would like to discuss this role please contact dan.woodcock@nds.ox.ac.uk. Applications for this vacancy are to be made online. You will be required to upload a supporting statement, setting out how you meet the selection criteria, curriculum vitae and the names and contact details of two referees as part of your online application. Please quote reference NDSA991 on all correspondence. Only applications received before noon Monday 14th September 2026 can be considered. Interviews will be held on week commencing Monday 28th September 2026.
Postdoctoral Data Scientist in Oxford employer: Corehr
Sheffield Hallam University is an exceptional employer, offering a vibrant and inclusive work culture that fosters innovation and collaboration within the Smart Interactive Technologies Lab. As a Research Fellow, you will have access to cutting-edge research infrastructure and the opportunity to contribute to impactful projects aimed at improving maternal health outcomes, all while benefiting from a supportive environment that prioritises professional growth and development. Join us in making a meaningful difference in healthcare through responsible and human-centred digital innovation.
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