Queen Mary University of London
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Postdoctoral Research Associate in Spatial Transcriptomics and Cancer Genomics at Queen Mary University of London Queen Mary University of London in United Kingdom
Degree Level
Postdoc
Field of study
Computer Science
Funding
Available
Deadline
Sep 14, 2026
Country
United Kingdom
University
Queen Mary University of London

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About this position
Queen Mary University of London is advertising a Postdoctoral Research Associate position in the Lockley group at the Barts Cancer Institute. The project focuses on Visium spatial transcriptomics and multiplexed immunohistochemistry to study the clonal evolution of resistance in high grade serous ovarian cancer. The successful candidate will lead the computational aspects of the work, strengthen informatics expertise in the team, and collaborate on developing new therapeutic approaches to target resistance evolution.
This opportunity is especially relevant for researchers with interests in cancer genomics, bioinformatics, computational biology, genomics, and translational cancer research. The role combines wet-lab and dry-lab work, with a strong emphasis on analysis of large-scale genomic data and R-based analysis. The institute highlights its broader cancer research environment and postgraduate training culture.
Eligibility highlights: a PhD or near-completion in biology, bioinformatics, computational biology, genomics, or a related field; experience in wet-lab and dry-lab research is beneficial; expertise in large-scale genomic data analysis and confidence in R are essential; ability to plan and critique independent work and supervise junior team members is expected.
Funding and benefits: the post offers a competitive salary, generous pension scheme, 30 days’ leave per year (pro-rata), season ticket loan, professional development opportunities, and flexible working arrangements.
Deadline: 14 September 2026. Apply via the Queen Mary jobs portal using the official application link.
Funding details
Available
What's required
A PhD, or near completion of one, in biology, bioinformatics, computational biology, genomics, or a relevant field, or equivalent research experience and qualifications. Experience in both wet-lab and dry-lab research is beneficial. Expertise in analysis of large-scale genomic data and confidence in R are essential. Candidates should be able to plan, deliver, and critique their own work, supervise students/junior team members, and work effectively within a broader team.
How to apply
Apply through the Queen Mary University of London jobs portal using the provided application link. Review the role details and submit your application before the deadline.
More information can be found here
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