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Bioinformatician​/Computational Biologist

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: The Francis Crick Institute Limited
Full Time position
Listed on 2026-09-22
Job specializations:
  • Research/Development
    Data Scientist, Research Scientist, Biomedical Science
Salary/Wage Range or Industry Benchmark: 49790 GBP Yearly GBP 49790.00 YEAR
Job Description & How to Apply Below
Location: Greater London

Bioinformatician/Computational Biologist

Contract term: This is a full-time, fixed term (5 years) position on Crick terms and conditions of employment.

Reporting to: Ilaria Malanchi, Principal Group Leader

Salary for this Role: From £49,790 with benefits, subject to skills and experience

About us

The Francis Crick Institute is Europe’s largest biomedical research institute under one roof. Our world-class scientists and staff collaborate on vital research to help prevent, diagnose and treat illnesses such as cancer, heart disease, infectious diseases and neurodegenerative conditions.

The Crick is a place for collaboration, innovation and exploration across many disciplines. A space where the brightest minds can pursue big and bold ideas and discover answers to crucial scientific questions. We support them in a dynamic environment which fosters excellence with state-of-the-art infrastructure, cutting-edge facilities, and a creative and curious culture. We’ve removed traditional boundaries of departments, divisions and disciplines and instead have an open approach that supports every researcher.

This gives us the freedom to take risks and carry out high-quality, pioneering research. Creating a space for discovery without boundaries helps us to turn our science into benefits for human health and the economy.

About the Malanchi Lab

The Tumour Host Interaction Lab, led by Professor Ilaria Malanchi, investigates how cancer cells interact with surrounding tissues and distant organs to create environments that support tumour growth, metastasis and treatment resistance.

Our research explores the relationship between cancer, ageing, inflammation and tissue regeneration, combining sophisticated experimental models with genomic and multi-omic approaches to uncover the mechanisms driving disease.

About the role

We are looking for a talented and motivated Bioinformatician to join our multidisciplinary team as part of a five-year ERC Synergy-funded research programme.

You’ll work with scientists across the project to analyse and integrate complex genomic, transcriptomic and epigenetic datasets, including bulk and single-cell RNA-seq, ATAC-seq, ChIP-seq, methylome and proteomic data.

This is more than a data analysis role. You’ll have the opportunity to influence experimental design, identify interesting patterns and signatures within large datasets and help translate computational findings into new biological hypotheses that can be tested experimentally.

You’ll join the Malanchi Lab at the Crick and collaborate closely with the groups of Professor Dominique Bonnet and Professor Francesca Ciccarelli as part of the wider ERC Synergy programme.

  • Analysing and integrating large-scale genomic and multi-omic datasets
  • Working with bulk and single-cell RNA-seq, ATAC-seq, ChIP-seq, methylome and proteomic data.
  • Developing computational approaches and algorithms to answer complex biological questions.
  • Identifying patterns and signatures within datasets and translating these into meaningful biological insights.
  • Working with scientists to inform experimental design and data interpretation.
  • Developing and maintaining bioinformatics tools, software and databases.
  • Ensuring data quality and integrity throughout the analysis process.
  • Communicating findings through project discussions, presentations, reports and publications.
  • Keeping up to date with emerging approaches and technologies across bioinformatics.
About you

You will have:

  • A degree in Bioinformatics, Computer Science or a related discipline, alongside a scientific background.*
  • Strong programming skills using languages such as Python, R, Java, C/C++ or Perl.*
  • Experience applying statistical methods to biological data.
  • Hands-on experience analysing next-generation sequencing,…
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