Postdoctoral Data Scientist

Corehr; Oxford; Hybrid; GBP 42,000 - 62,000; Full time

Job summary

Corehr, based at Old Road Campus, University of Oxford, seeks a data scientist or bioinformatician to analyse a large multiomic prostate cancer dataset and identify genetic features linked to treatment susceptibility. The role is full-time and fixed-term until 31st December 2027, with potential regular remote working arranged with the line manager.

Applicants should have a PhD/near completion in a quantitative field and strong programming, data analysis, and ML skills.

Qualifications

• PhD/DPhil in Mathematics, Statistics, Computer Science, Bioinformatics, Physics, Engineering, or related.
• Strong programming and data analysis skills with ML experience.
• Experience with multiomic data and cancer biology desirable.
• Ability to publish and present findings.
• Experience with DNA/RNA sequencing data processing.

Responsibilities

• Analyse expansive multiomic prostate cancer data set.
• Identify features for integration with clinical trial data.
• Communicate results to collaborators across the project.
• Work independently and with the project team.
• Contribute to publications and presentations.

Skills

Programming & data analysis

Machine learning

Bioinformatics knowledge

Education

PhD/DPhil in Mathematics, Statistics, Computer Science, Bioinformatics, Physics, Engineering, or related

Tools

Bioinformatics tools for sequencing analysis

Job description

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 (www.panprostate.org), 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 [e-mail]

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

Committed to equality and valuing diversity