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Research Fellow​/Senior Research Fellow – Computational Biologist; Cancer Evolution Scientist

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: RFCSR
Full Time position
Listed on 2026-06-05
Job specializations:
  • Research/Development
    Research Scientist, Data Scientist
Salary/Wage Range or Industry Benchmark: 80000 - 100000 GBP Yearly GBP 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Research Fellow / Senior Research Fellow – Computational Biologist (Cancer Evolution Scientist)
Location: Greater London

Research Fellow / Senior Research Fellow – Computational Biologist (Cancer Evolution Scientist)

University College London (UCL) invites applications for a Research Fellow or Senior Research Fellow position in Computational Biology, focusing on cancer evolution science. This role is based within a leading interdisciplinary research environment dedicated to advancing understanding of cancer biology through computational and data-driven approaches.

The successful candidate will contribute to cutting‑edge research in cancer evolution, leveraging computational biology, bioinformatics, and quantitative modelling to investigate tumour development, progression, and heterogeneity. The role involves integrating large‑scale genomic and multi‑omics datasets to understand evolutionary dynamics in cancer and identify clinically relevant insights.

The postholder will work closely with multidisciplinary teams comprising computational biologists, clinicians, and experimental scientists. Responsibilities include designing and implementing computational models, analysing complex biological datasets, contributing to high‑impact publications, supporting grant development, and presenting research findings at national and international conferences. The role also involves mentoring junior researchers and contributing to collaborative research initiatives within UCL’s cancer research ecosystem.

The position offers an opportunity to work within a globally recognised research institution with strong expertise in computational oncology, systems biology, and translational cancer research. The role supports both methodological innovation and applied biomedical research aimed at improving cancer diagnosis, prognosis, and treatment strategies.

Eligibility Criteria
  • PhD in Computational Biology, Bioinformatics, Mathematics, Physics, Computer Science, Cancer Biology, or a related discipline
  • Strong research background relevant to cancer evolution or computational oncology
  • Demonstrated experience in analysing large-scale biological or genomic datasets
  • Evidence of peer-reviewed publications in relevant research areas
  • Experience appropriate to either postdoctoral (Research Fellow) or more advanced (Senior Research Fellow) level
  • Ability to work within multidisciplinary research environments
  • Strong track record of independent research contribution
Required Expertise / Skills
  • Strong computational and quantitative modelling skills
  • Experience with cancer genomics, tumour evolution, or systems biology
  • Proficiency in programming languages such as Python, R, or similar analytical tools
  • Expertise in bioinformatics pipelines and multi-omics data analysis
  • Strong statistical analysis and data interpretation skills
  • Ability to develop and apply computational models to biological systems
  • Excellent scientific writing and communication skills
  • Experience in publishing research in high-impact peer-reviewed journals
  • Ability to collaborate effectively with clinical and experimental research teams
  • Capacity to contribute to grant writing and research leadership activities
Salary Details

Salary will be in accordance with UCL Research Fellow / Senior Research Fellow pay scales and will depend on experience and academic track record.

Final date to receive applications

Not specified in the provided listing; applications will be considered according to UCL recruitment timelines and departmental requirements.

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Position Requirements
10+ Years work experience
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