Head of Translational Bioinformatics

BioTalent • United Kingdom
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AI Summary

Lead a team of bioinformatics scientists to generate actionable insights from multi-omic profiling of patient samples and in vitro/in vivo translational models. Shape bioinformatics strategy and contribute to the wider R&D digital and data science vision. Collaborate with biology-focused research teams and external partners to advance drug discovery and disease biology.

Key Highlights
Lead a team of bioinformatics scientists
Shape bioinformatics strategy
Collaborate with biology-focused research teams and external partners
Key Responsibilities
Lead and develop a bioinformatics function tightly integrated with biology and translational research
Define bioinformatics strategy and contribute to broader data science and digital R&D strategy
Provide scientific leadership, mentorship, and technical direction to the team
Technical Skills Required
Bioinformatics Computational Biology Genomics Immunology Multi-omics analysis Single-cell RNA-seq Spatial transcriptomics Genetic data integration HPC Cloud platforms Containerisation (Docker)
Benefits & Perks
Relocation options open
UK relocation options available
Nice to Have
Gene therapy experience

Job Description


Head of Translational Bioinformatics

UK- relocation options open


We are seeking an experienced and forward-thinking Head of Translational Bioinformatics to join a Data Science & Analytics Leadership Team. This is a senior role for a scientifically driven leader who is passionate about using data to unlock disease biology and accelerate drug discovery.


About the Role

In this role, you will lead a high-performing team of bioinformatics scientists, generating actionable insight from multi-omic profiling of patient samples and in vitro / in vivo translational models, in close partnership with biology-focused research teams.

You will play a key role in shaping bioinformatics strategy, advancing state-of-the-art methodologies, and contributing to the wider R&D digital and data science vision. Your work will directly support research programmes in immunology and inflammatory disease, spanning areas such as dermatology, senescence, and immune modulation.

A critical element of the role is the deep integration of bioinformatics within drug discovery and platform teams, working alongside multidisciplinary scientists to design, execute, and interpret omics studies that drive target discovery, validation, and translational decision-making.


Who You’ll Work With

  • Lead and mentor a team of bioinformatics scientists
  • Partner closely with biology focus areas, platform leads, and senior research leadership
  • Collaborate with internal data science and digital leaders across R&D
  • Initiate and contribute to external collaborations with academic, commercial, and industry partners to expand access to human data and cutting-edge methods


What You’ll Do

  • Lead and develop a bioinformatics function tightly integrated with biology and translational research
  • Define bioinformatics strategy and contribute to broader data science and digital R&D strategy
  • Provide scientific leadership, mentorship, and technical direction to the team
  • Deliver mechanistic insight from patient-derived molecular profiling and disease models
  • Drive innovation in bioinformatics methods, data visualisation, and predictive/generative modelling
  • Provide authoritative scientific input into drug discovery projects and governance forums
  • Embed bioinformatics capability within therapeutic project teams to influence decision-making and translational packages


What We’re Looking For

  • PhD (or equivalent) in Bioinformatics, Computational Biology, Genomics, Immunology, or a related discipline
  • 10+ years’ industry experience, ideally within pharmaceutical or biotech R&D
  • Proven experience leading and mentoring teams of 5–10 scientists
  • Strong track record of applying bioinformatics to drug discovery and disease biology, with immunology expertise essential
  • Deep expertise in multi-omics analysis, with strong preference for:
  • Single-cell RNA-seq
  • Spatial transcriptomics
  • Genetic data integration to identify causal biology
  • Experience supporting translation from discovery into clinical development, including biomarker strategy and back-translation
  • Exposure to multiple drug modalities (gene therapy experience advantageous)
  • Hands-on experience with HPC, cloud platforms, and containerisation (e.g. Docker) for reproducible workflows


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