About the role
About Relation Relation is a sector defining TechBio 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 from patient tissue, functional assays, and machine learning to drive disease understanding, from cause to cure. We are scaling rapidly and building a team of exceptional individuals to push the boundaries of drug discovery. You will work in highly interdisciplinary teams where biology, computation, and engineering come together to solve complex problems that have not been solved before. Our state-of-the-art wet and dry labs in the heart of London are designed to accelerate this integration and translate insight into impact. We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age. By joining Relation, you will help define how medicines are discovered and deliver meaningful impact for patients. The opportunity This is a unique opportunity for a data scientist to work on multi-omics data to drive transformative insights into drug discovery. As a member of the Cross Indication team, you will contribute to identifying and validating drug targets through advanced data analysis and innovative computational approaches. The Cross Indication team collaborates across both Relations internal and partnership programmes, applying state-of-the-art computational methods to integrate diverse datasets. By combining biological insights with advanced data analytics,
the team drives target discovery and validation initiative. Day to day, you will Develop and implement robust computational workflows for the integration and analysis of multi-omics datasets, including single-cell and/or spatial modalities. Design and apply statistical and computational models for analysing transcriptomics and related omics data. Use biological insight and data intuition to design meaningful, challenging evaluation tasks for ML models. Collaborate closely with ML researchers to inform and iterate on model architectures and assumptions. Partner with experimental scientists to help formulate, test, and validate computational hypotheses. Communicate findings clearly through internal presentations and contribute to scientific publications. Professionally, you will have A PhD in computational biology, bioinformatics, statistics, physics, mathematics, or a related quantitative discipline. Strong experience analysing high-dimensional biological data, including transcriptomics and other omics datasets. Proficiency in Python, with experience working in high-performance or cloud computing environments.