Senior Machine Learning Scientist (Generative Modelling)

About the role

Relation is seeking a Machine Learning Scientist to build generative and predictive models of cellular behaviour to advance drug discovery. You will work in an interdisciplinary team to develop models that learn intervention effects from complex biological data, focusing on causal coherence and mechanistic fidelity. This role involves collaborating with experimental teams to validate computational hypotheses and guide real-world therapeutic strategies.

Responsibilities

• Design and implement generative modelling approaches that learn intervention effects from diverse biological data, including single-cell perturbation experiments.
• Develop models that go beyond correlation, focusing on generalisation, counterfactual prediction, and experimental design.
• Collaborate with experimental teams to design and validate computational hypotheses via iterative strategies that identify the highest-signal next experiment.
• Evaluate models not just for fit, but for causal coherence, mechanistic fidelity, and utility in guiding real-world interventions.
• Communicate findings clearly to colleagues and stakeholders from different disciplines.

Required skills

• Machine Learning
• Generative modelling
• Probabilistic modelling
• Representation learning
• Neural network architectures
• Python
• High-performance computing

Nice to have

• Single-cell data analysis
• Perturbational datasets

Qualifications

• PhD in ML, statistics, computer science, or a related quantitative field

About the Company

Relation is a sector-defining TechBio company developing transformational medicines by leveraging single-cell multi-omics, functional assays, and machine learning. The company operates in a matrixed, interdisciplinary environment with state-of-the-art wet and dry labs in London.