Associate Director - Computational Genomics
Relation Therapeutics
Location
London
Employment Type
Full time
Department
Data Science/Computational Biology
About Relation
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.
The Opportunity
This is a unique opportunity for an Associate Director to lead and shape statistical, population genomics, and multi-omics efforts to accelerate target identification and validation across multiple therapeutic areas. In this role, you will work with large-scale human genetics resources (e.g. biobanks and population cohorts) and/or multi-omics datasets, applying cutting-edge statistical genetics, computational biology, and machine learning approaches to generate actionable biological insights.
As part of the Cross-Indication team, you will operate at the interface of human genetics, computational biology, and machine learning, translating genetic and multi-modal evidence into target prioritisation frameworks, mechanistic hypotheses, and data-driven decision-making across the organisation. You will play a key role in developing and overseeing robust, scalable, and reproducible analysis pipelines, ensuring that genetic and multi-omics insights are effectively integrated into programme strategy and portfolio decisions.
Your responsibilities
Lead statistical and/or population genomics analyses using large-scale human genetic datasets to support target discovery and validation.
Develop and implement scalable computational workflows for reproducible analysis of genomics, transcriptomics, and other multi-omics datasets.
Design and apply statistical genetics and/or statistical modelling methodologies, including (but not limited to):
GWAS, fine-mapping, colocalisation
Polygenic risk scoring
Rare variant analyses
Functional annotation
And/or causal inference approaches such as Mendelian randomisation
Lead multi-modal data integration efforts, combining human genetics with transcriptomics, proteomics, and other omics to uncover disease biology and prioritise actionable targets.
Partner closely with experimental, translational, and machine learning teams to validate hypotheses, interpret results, and guide downstream studies.
Communicate findings clearly and confidently to internal stakeholders, including presenting methods, results, risks/limitations, and recommendations.
Contribute to publications, scientific communications, and project documentation, supporting scientific excellence and external visibility.
Professionally, you have
PhD in statistical genetics, genomics, computational biology, bioinformatics, or a related quantitative discipline.
Post-PhD experience, ideally including time in industry, biotech, and/or pharmaceutical environments.
Strong track record in statistical genetics and/or computational biology, with experience analysing large-scale human genetics and/or multi-omics datasets, including transcriptomics.
High proficiency in Python (preferred) and R, with experience working in high-performance computing environments.
Ability to operate independently at a senior level, providing technical leadership and driving projects from concept through delivery.
Desirable knowledge or experiences
Familiarity with single-cell transcriptomics and/or patient-derived datasets.
Experience working in interdisciplinary teams within biotech or pharma settings.
Knowledge of machine learning techniques applied to biological data.
Background in statistical modelling, algorithm development, and/or causal inference frameworks.
Strong understanding of the end-to-end drug discovery process and how genetic and multi-omics evidence informs decision-making.
Personally, you are
Inclusive leader and collaborative team player.
Clear, confident communicator.
Driven by impact and motivated by meaningful scientific outcomes.
Humble, curious, and eager to learn.
Passionate about improving patient outcomes.
Comfortable working in dynamic, fast-paced environments..
Join us in this exciting role where your contributions will have a direct impact on advancing our understanding of genetics and disease risk, supporting our mission to get transformative medicines to patients. Together, we're not just doing research; we're setting new standards in the field of machine learning and genetics. The patient is waiting!
Relation Therapeutics is a committed equal opportunities employer.
RECRUITMENT AGENCIES: Please note that Relation Therapeutics does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation Therapeutics will not be liable for any fees associated with unsolicited CVs.