Senior Data Scientist (Single Cell)

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

Build next-generation generative and predictive models of cellular behavior using single-cell multi-omics. Process and QC paired single-cell RNA-seq and scATAC-seq at scale, develop Nextflow pipelines for custom chemistries, and create multimodal training datasets integrating proteomics and high-content imaging. Work with wet lab scientists to ensure experiments are analytically tractable, evaluate model performance with biology sanity checks, and present findings to drive publications.

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FursaFursa
Relation
Relation
14 hours ago

Senior Data Scientist (Single Cell)

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Last checked: 5 hours agoStatus: Live

Job Summary

Build next-generation generative and predictive models of cellular behavior using single-cell multi-omics. Process and QC paired single-cell RNA-seq and scATAC-seq at scale, develop Nextflow pipelines for custom chemistries, and create multimodal training datasets integrating proteomics and high-content imaging. Work with wet lab scientists to ensure experiments are analytically tractable, evaluate model performance with biology sanity checks, and present findings to drive publications.
Location: London
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Process and QC paired single-cell RNA-seq and scATAC-seq at scale from thousands of perturbations across diverse cell types and contexts.
  • •Develop and maintain Nextflow pipelines compatible with custom combinatorial indexing chemistries, including STARsolo, Alevin-fry, Chromap, and SnapATAC2.
  • •Integrate scRNA-seq and scATAC-seq with extracellular proteomics and high-content imaging to build multimodal training datasets.
  • •Manage data in memory-efficient formats (e.g., Zarr) for GPU-accelerated processing and scalable model training.
  • •Collaborate with ML modelers to develop architectures, evaluate models with biological sanity checks, and present findings for internal stakeholders and publications.

Key Requirements

  • •A PhD (or equivalent industry experience) in computational biology, bioinformatics, or a related quantitative field.
  • •Deep hands-on experience processing and analyzing large-scale single-cell multiomics data, ideally paired RNA + ATAC.
  • •Proficiency with single-cell analysis toolkits (e.g., scverse ecosystem) and workflow management (Nextflow, Snakemake).
  • •Experience with arrayed CRISPR perturbation screen data, including sample hashing, perturbation QC, and single-cell effect quantification.
  • •Proficiency in Python and familiarity with high-performance computing environments.
Experience:Single-cell multiomicsComputational biologyBioinformaticsMachine learningCRISPR screening
Education:PhD / Doctorate in computational biology, bioinformatics, or a related quantitative field
Skills:CommunicationCollaborationProblem-solvingOwnershipResilience
Tech Stack:PythonNextflowSnakemakeSTARsoloAlevin-fryChromapSnapATAC2ZarrGPUHPC

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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