Snr Data Scientist, Computational Genomics/DNA Modelling

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

Work in an interdisciplinary Rosalind team to build and evaluate computational models that link DNA sequence and genetic variation to gene regulation and disease biology. Develop sequence and regulatory-element machine learning models for tasks like variant effect and regulatory activity prediction, and integrate sequence-derived representations with transcriptomic, epigenomic, and perturbation data. Partner with experimental researchers, communicate results clearly, and contribute to publications and project documentation.

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Relation
Relation
2 months ago

Snr Data Scientist, Computational Genomics/DNA Modelling

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Last checked: 22 hours agoStatus: Live

Job Summary

Work in an interdisciplinary Rosalind team to build and evaluate computational models that link DNA sequence and genetic variation to gene regulation and disease biology. Develop sequence and regulatory-element machine learning models for tasks like variant effect and regulatory activity prediction, and integrate sequence-derived representations with transcriptomic, epigenomic, and perturbation data. Partner with experimental researchers, communicate results clearly, and contribute to publications and project documentation.
Location: London
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Sr. Manager level

Key Responsibilities

  • •Develop and implement machine learning models for DNA sequence, regulatory elements, and genetic variation in disease-relevant contexts.
  • •Build, evaluate, and benchmark models for sequence-to-function tasks such as variant effect prediction and regulatory activity prediction.
  • •Integrate sequence-derived representations with transcriptomic, epigenomic, and perturbational datasets to uncover disease mechanisms and support target prioritisation.
  • •Partner closely with experimental and machine learning researchers to validate hypotheses and guide downstream studies.
  • •Communicate findings to internal stakeholders and contribute to publications, scientific communications, and project documentation.

Key Requirements

  • •PhD in computational biology, machine learning, statistics, genomics, bioinformatics, or a related quantitative discipline.
  • •Post-PhD experience, ideally including time in an industry, biotech, or pharmaceutical environment.
  • •Experience with DNA language models, genomic foundation models, or transformer-based sequence models.
  • •Strong understanding of statistical machine learning and probabilistic modelling, with experience selecting and evaluating approaches for complex biological datasets.
  • •High proficiency in Python (preferred) and R, with experience in high-performance computing environments.
Experience:BiotechPharmaceuticalGenomicsComputational biology
Education:PhD / Doctorate in computational biology, machine learning, statistics, genomics, bioinformatics
Skills:CommunicationStakeholder managementIndependenceOwnershipCollaboration
Tech Stack:PythonRMachine learningDNA language modelsTransformer-based sequence modelsHigh-performance computingHi-CCapture-C

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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