Data Scientist – Computational Genomics, 12-month FTC

Relation
London
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningEducation: phdSkills: ["Communication","Collaboration","Stakeholder management","Ownership","Resilience"]

Build and deploy machine-learning methods at the genomics–ML interface to accelerate target identification and validation. Apply statistical modeling to genomics, transcriptomics and other multi-omics datasets, integrate human genetics evidence with OMICs, and develop scalable, reproducible computational workflows. Partner with experimental and ML researchers, communicate findings to stakeholders, and contribute to publications and project documentation in Relation’s interdisciplinary drug discovery teams based in London.

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Relation
Relation
2 months ago

Data Scientist – Computational Genomics, 12-month FTC

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Last checked: 10 hours agoStatus: Live

Job Summary

Build and deploy machine-learning methods at the genomics–ML interface to accelerate target identification and validation. Apply statistical modeling to genomics, transcriptomics and other multi-omics datasets, integrate human genetics evidence with OMICs, and develop scalable, reproducible computational workflows. Partner with experimental and ML researchers, communicate findings to stakeholders, and contribute to publications and project documentation in Relation’s interdisciplinary drug discovery teams based in London.
Location: London
Workplace: Onsite
Employment Type: Full time · 12 months
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Apply, build, refine, and integrate statistical models to extract insight from genomics, transcriptomics, and other OMICs datasets to support target discovery and validation.
  • •Work cross-functionally at the ML-genetics interface to identify opportunities, solve problems, and implement shared solutions.
  • •Integrate human genetics evidence with OMICs datasets (e.g., transcriptomics, proteomics) to uncover disease mechanisms and prioritize actionable targets.
  • •Develop scalable computational workflows for reproducible analysis within Relation’s existing stack.
  • •Partner with experimental and machine learning researchers to validate hypotheses and communicate results to internal stakeholders; contribute to publications and documentation.

Key Requirements

  • •PhD in statistical genetics, genomics, computational biology, machine learning, bioinformatics, or a related quantitative field.
  • •Knowledge of machine learning techniques applied to biological data.
  • •Experience in quantitative genomics, statistics, bioinformatics, or multi-omics data analysis.
  • •Proficiency in Python (preferred) or R, with familiarity with high-performance computing and collaborative coding/version control (e.g. git).
  • •Bonus: familiarity with single-cell transcriptomics or patient-derived datasets, or experience in interdisciplinary/matrixed biotech/pharma teams.
Experience:BiotechPharmaMulti-omicsSingle-cell transcriptomicsComputational biology
Education:PhD / Doctorate
Skills:CommunicationCollaborationStakeholder managementOwnershipResilience
Tech Stack:PythonRGitHigh-performance computingMachine learning

Company Brief

Relation
Relation (Relation Therapeutics) is a UK-based, technology-enabled biopharmaceutical company that combines single-cell multi-omics, patient-derived tissue, functional assays and machine learning to discover and develop novel therapeutics across immunology, metabolic and bone diseases.
Industry: Biotech
Company Size: Medium (51 to 250 employees)
Growth: Early Stage Startup
Valuation: USD 100M to 250M
Funding: Seed
Headquarters: London, United Kingdom
Founded: 2019
Glassdoor
Glassdoor: 3.8
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