Director, Data Science - Computational Genomics
Location: London, UK (hybrid)
Relation is an end-to-end biotech company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics directly from patient tissue, functional assays, and machine learning to drive disease understanding—from cause to cure.
This year, we embarked on an exciting dual collaboration with GSK to tackle fibrosis and osteoarthritis, while also advancing our own internal osteoporosis programme. By combining our cutting-edge ML capabilities with GSK’s deep expertise in drug discovery, this partnership underscores our commitment to pioneering science and delivering impactful therapies to patients.
We are rapidly scaling our technology and discovery teams, offering a unique opportunity to join one of the most innovative TechBio companies. Be part of our dynamic, interdisciplinary teams, collaborating closely to redefine the boundaries of possibility in drug discovery. Our state-of-the-art wet and dry laboratories, located in the heart of London, provide an exceptional environment to foster interdisciplinarity and turn groundbreaking ideas into impactful therapies for patients.
We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the grounds of gender, sexual orientation, marital or civil partner status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age. We cultivate innovation through collaboration, empowering every team member to do their best work and reach their highest potential.
By joining Relation, you will become part of an exceptionally talented team with extraordinary leverage to advance the field of drug discovery. Your work will shape our culture, strategic direction, and, most importantly, impact patients’ lives.
Opportunity
We’re now hiring a Director of Statistical Genetics & Functional Genomics to lead a growing team that integrates human genetics, functional genomics, and computational methods to drive novel target discovery. This is a rare opportunity to help shape our therapeutic pipeline by unlocking the causal mechanisms of disease from human data.
Your responsibilities
- Lead and grow a high-performing team applying cutting-edge statistical genetics and computational genomics to uncover causal mechanisms in complex traits and diseases.
- Design and implement integrative analysis frameworks combining GWAS, PheWAS, and fine-mapping with functional genomic datasets (e.g. eQTLs, chromatin accessibility, single-cell perturbation) to prioritise causal genes, pathways, and cell types.
- Leverage single-cell and spatial transcriptomics to map disease-relevant cellular states and tissue-specific regulatory architecture.
- Collaborate cross-functionally with disease biology, target discovery, and experimental teams to translate genetic insights into testable hypotheses and novel therapeutic concepts.
- Stay at the forefront of emerging methods in statistical genetics and variant-to-function inference, guiding internal adoption and development.
- Contribute to platform strategy and target identification efforts across multiple disease areas.
- Foster a culture of scientific rigour, collaboration, and innovation—while mentoring junior scientists and supporting their continued development.
Who you are
- You bring deep expertise in human statistical genetics, including fine-mapping, LD structure, polygenic risk scoring, partitioned heritability, and causal inference methods (e.g. Mendelian Randomisation).
- You have experience integrating multi-modal data—including GWAS, transcriptomic (bulk and single-cell), epigenomic (ATAC-seq, ChIP-seq), and proteomic datasets—to identify causal genes and pathways.
- You’re fluent in Python, R, or similar languages, and comfortable working in a high-performance computing environment.
- You’ve led scientific projects and teams, and enjoy mentoring others while setting a high bar for excellence.
- You’ve worked closely with cross-functional teams to turn computational findings into actionable biological insights, ideally within a drug discovery or translational context.
- Experience developing or applying machine learning or Bayesian approaches for variant-to-function inference is a plus.
- You’re familiar with large-scale genomic resources (e.g. UK Biobank, GTEx, gnomAD, Open Targets) and their application in human disease research.
Personally, you are
- Inclusive leader and team player.
- Clear communicator.
- Driven by impact.
- Humble and hungry to learn.
- Motivated and curious.
- Passionate about making a difference in patients’ lives
Join us in this exciting role, where your contributions will directly impact advancing our understanding of genetics and disease risk, supporting our mission to deliver transformative medicines to patients. Together, we’re not just conducting research—we’re setting new standards in the fields of machine learning and genetics. The patient is waiting!
Relation is a committed equal opportunities employer.
RECRUITMENT AGENCIES: Please note that Relation does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation will not be liable for any fees associated with unsolicited CVs.
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