Senior Staff AI Scientist, AI Reasoning Full-time NEW

AI ACCELERATOR

Most diseases are still poorly understood at a biological level. Despite decades of research, the causal mechanisms driving many conditions remain unclear, limiting our ability to identify the right targets, design the right interventions and bring the right medicines to patients.

The AI Accelerator exists to change that. Based in London and sitting within Computational Innovation, the Accelerator's mission is to provision reusable, state-of-the-art AI capabilities that deepen our understanding of disease biology and increase the probability of discovering and developing an innovative medicine.

We do this by applying neural-based methods across the biomedical data landscape to integrate heterogeneous, multimodal data sources, infer biological relationships and embed causal thinking into what we build. The goal is not just to predict but to explain and understand why disease occurs.

A core component of the AI Accelerator is the AI Reasoning team that focusses on causality and rationalising model outputs so our subject matter experts can confidently interrogate, trust and act on model-generated hypotheses.

THE POSITION

We are looking for a Senior Staff AI Scientist in the AI Reasoning team who will focus on how the Accelerator uses curated knowledge and agents to strengthen, contextualise and rationalise model outputs, transforming them into trusted scientific hypotheses.

You will use state-of-the-art large language models, AI assistants and agents, curated knowledge bases and evidence-retrieval capabilities to explain and rationalise AI Accelerator model outputs, providing the interpretability layer that builds trust in model-generated hypotheses. You will report to the Director, AI Reasoning, sit on the AI Reasoning Leadership Team and contribute to AI Reasoning strategy.

You will be an experienced matrix leader who influences through multidisciplinary squads, setting scientific standards and evaluation criteria, providing technical mentorship and representing the domain in cross-organisational fora. You will also serve as the AI Accelerator's senior scientific bridge to Computational Innovation's portfolio-facing teams ensuring that what we build reflects real biology and disease understanding, and that domain expertise flows back into capability design.

Key Responsibilities

• Translate strategy into a scientific roadmap, priorities and success criteria for evidence-grounded AI, and drive delivery against them.
• Strengthen AI-generated hypotheses by combining model findings with supporting and contradictory evidence, provenance and biological context, so scientists can judge credibility and prioritise follow-up.
• Lead the development of evaluation and benchmarking approaches, defining what makes evidence credible and traceable, and when a hypothesis is robust enough to inform portfolio decisions.
• Partner with computational biology and human genetics to ensure the work meets real disease-biology and target-evaluation needs, supports adoption into scientific workflows, and complements rather than duplicates existing evidence.
• Provide senior matrix leadership and scientific judgement to inform build, buy and partner decisions, mentor scientists across teams, contribute to Accelerator-wide priorities, and build external credibility in AI-assisted scientific reasoning and evidence synthesis.

Required Qualifications

• PhD in Computational Biology, Bioinformatics, Machine Learning or a closely related field.
• Industry experience in pharma, techbio or AI-native drug discovery organisations and an understanding of target identification, patient stratification, biomarker discovery, translational biology and how scientific evidence informs portfolio decision-making.
• Experience using modern AI tools for scientific work, for example large language models, scientific AI assistants and agents, retrieval-augmented reasoning, curated knowledge bases, ontologies, pathway resources or biomedical knowledge graphs.
• Track record of setting direction across teams without formal authority, mentoring senior AI scientists and shaping the priorities of adjacent teams.
• Excellent written and verbal communication, with the ability to translate between AI and biology audiences and to represent the Accelerator credibly in senior scientific and business fora.

Preferred Qualifications

• A sufficient understanding of AI model development to engage deeply with AI Scientists and Research Engineers on design and evaluation trade-offs.
• Experience assessing build/buy/co-develop options for scientific AI capabilities and building scientific work packages with external partners.
• Familiarity with regulatory expectations around AI-derived evidence in life sciences.

This is a hybrid role with 4 days a week in the office.

WHY THIS IS A GREAT PLACE TO WORK

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