to run semi-technical interviews, assessing how candidates apply knowledge, explain ideas, and contribute in practice. Bonus: Experience hiring across other technical roles, including data scientists (especially those using probabilistic models), data engineers, product managers, and front-end or full-stack developers. Ability to test new sourcing tools and methods, and adapt based on evidence and feedback. Confidence using More ❯
to run semi-technical interviews, assessing how candidates apply knowledge, explain ideas, and contribute in practice. Bonus: Experience hiring across other technical roles, including data scientists (especially those using probabilistic models), data engineers, product managers, and front-end or full-stack developers. Ability to test new sourcing tools and methods, and adapt based on evidence and feedback. Confidence using More ❯
a team with access to cutting-edge multiomic and interventional datasets, advanced computational infrastructure, and deep interdisciplinary expertise. This is an opportunity to push the boundaries of what causal modelling can achieve in complex, high-dimensional, and noisy real-world systems, and to see your work tested directly in experimental biology. Your responsibilities Collaborate with domain experts to translate … biological hypotheses into formal causal modelling problems. Design and implement causal learning approaches that capture regulatory logic, cell fate trajectories, and 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 … science or a related quantitative field. Deep expertise in causal inference, such as causal graphical models, counterfactual reasoning, or invariant representation learning. Strong background in one or more of probabilisticmodelling, time series analysis, or dynamical systems. Proficiency in Python and familiarity with scalable ML tooling and high-performance computing. Desirable knowledge or experiences Familiarity with biological datasets More ❯
