About RelationRxRelationRx is a groundbreaking TechBio organization at the forefront of developing transformative medicines, driven by advanced technology. Our mission is to gain unprecedented insights into human biology and discover therapies for some of the most challenging diseases. We harness the power of single-cell multi-omics, functional assays, and machine learning to enhance our understanding of diseases from their origins to potential cures.As we rapidly expand, we are assembling a team of extraordinary individuals dedicated to redefining the landscape of drug discovery. You will collaborate within highly interdisciplinary teams where biology, computation, and engineering intersect to tackle complex, unsolved problems. Our cutting-edge labs in central London are designed to facilitate this integration and translate insights into tangible impacts.We are devoted to fostering diverse and inclusive teams. RelationRx is an equal opportunity employer and does not discriminate based on gender, sexual orientation, marital status, gender reassignment, race, color, nationality, ethnic or national origin, religion or belief, disability, or age.By joining RelationRx, you will play a crucial role in shaping the future of medicine discovery and making a significant impact on patients' lives.The OpportunityRelationRx presents an exceptional opportunity for a Machine Learning Scientist to contribute to the development of next-generation generative and predictive models focused on cellular behavior. Your contributions will be pivotal in our efforts to comprehend and influence cellular decision-making, enabling innovative therapeutic strategies rooted in generative models.You will be part of a team equipped with state-of-the-art multiomic and interventional datasets, advanced computational tools, and extensive interdisciplinary expertise. We embrace contemporary machine learning methodologies, including agentic workflows, to expedite research iterations. This role offers the chance to expand the horizons of generative modeling in complex, high-dimensional, and noisy real-world systems while directly applying your work in experimental biology.Your Daily ResponsibilitiesDesign and implement generative modeling techniques that learn intervention effects from diverse biological datasets, including single-cell perturbation experiments.Create models that go beyond mere correlation, emphasizing generalization, counterfactual prediction, and experimental design.Collaborate with experimental teams to develop and validate computational hypotheses through iterative strategies aimed at identifying the most significant next experiments.
Apr 30, 2026