Director of AI Reasoning
The Position
We are seeking a senior leader of AI Reasoning to join a Computational Innovation AI function (@computationalinnovation) that will deliver next generation foundational AI capabilities to support the discovery and development of innovative medicines.
A core component of the AI function is AI Reasoning, a team focussed on moving beyond identifying patterns in data to finding real relationships and explaining model decisions. The AI Reasoning team will develop and apply state-of-the-art approaches in causal discovery and inference, mechanistic modelling, model rationalisation and uncertainty quantification to answer not just what may happen, but why and with what level of confidence.
In this role, you will hire and lead a team of world-class researchers working at the intersection of machine learning, statistics and biology. In close partnership with the AI Systems team, the Director of AI Reasoning will co-design architectures where causality, explainability and calibrated uncertainty are built into foundation models from the outset, rather than treated as an afterthought.
The successful candidate will be part of the senior leadership team and play a key role in shaping the AI strategy and delivering on the mission. This is a unique opportunity to be part of a critical strategic initiative for a pharmaceutical company that invests heavily in research and development to discover and develop innovative therapies that can improve and extend lives in areas of high unmet medical need.
Key Responsibilities
• Grow and lead a team focused on developing innovations in causal discovery and inference, mechanistic modelling and interpretable and explainable AI applied to biology
• Contribute to building and running the AI function, defining AI strategy and ensuring success through delivery of AI Reasoning capabilities that align with AI function goals and translate to portfolio impact
• Design and implement approaches that move beyond correlation to identify causal relationships in biological systems and simulate interventional effects
• Partner closely with the AI Systems team to co-design foundation model architectures where causal reasoning, explainability and uncertainty quantification are integral to model design, training and evaluation
• Establish rigorous uncertainty quantification frameworks and validation strategies to support confident decision-making across the portfolio
• Translate AI Reasoning methodologies into applied impact through close collaboration with Applied Analytics and AI, maximising programme success rates
• Drive operational excellence across AI Reasoning initiatives, setting standards for evidence, validation and scientific rigour
• Build and leverage partnerships with leading academic and industry collaborators as key force multipliers
• Publish AI Reasoning research at top-tier venues to attract and retain exceptional talent while remaining true to the mission of increasing probability of success
• Requirements
• PhD in Machine Learning, Statistics, Computational Biology or a related field
• Deep expertise in causal discovery and inference, mechanistic modelling and uncertainty quantification. Expertise in hybrid approaches such as neurosymbolic AI or physics-informed AI is advantageous
• Experience setting research strategy and translating strategy into execution with measurable scientific and portfolio impact
• Proven experience building and leading high-performing innovation teams, including leading leaders and mentoring junior staff
• Strong track record of translating innovation into impact, including publications and applied methods adopted in practice
• Ability to distinguish correlation from causation and guide stakeholders toward robust causal reasoning
• Ability to explain complex AI and statistical concepts to non-specialist audiences, including biologists and senior leaders
• Strong writing skills for both scientific publications and internal documentation
• Comfortable presenting to technical and non-technical audiences