The Position

We are seeking a Senior Staff AI Scientist to join a Computational Innovation AI department (@computationalinnovation) that will deliver next generation foundational AI capabilities to support discovery and development of innovative medicines.

A core component of the AI department is AI Systems, a team focused on designing, building and deploying versatile biomedical foundation models that, through adaptation, can enhance human understanding of disease biology and help identify potential targets, biomarkers and patient segments for further research.

The Senior Staff AI Scientist is an experienced individual scientific leader in AI Systems who defines architectural direction, pioneers novel approaches and tackles the hardest research problems through deep hands-on expertise.

In this role, you will focus on advancing the state of the art in biomedical foundation models through architectural innovation, rigorous experimentation and close partnership with ML Engineers who optimise model components and translate model prototypes into production

systems. The Senior Staff AI Scientist designs with downstream application in mind, ensuring architectures respect biomedical data structure and complexity and can be adapted and deployed for portfolio impact across therapeutic areas.

The successful candidate will be a senior research authority within AI Systems and a core contributor to innovation strategy setting and capability roadmap building. Free from line management responsibilities, this role exists to maximise scientific impact: shaping what the organisation builds, establishing research patterns others follow, influencing strategy and building external scientific credibility, all while remaining deeply hands-on with the most complex technical challenges.

Key Responsibilities

• Define and influence AI Systems innovation direction through identification of promising architectural approaches and strategic scientific bets
• Design and prototype novel biomedical foundation model architectures, including sophisticated multi-modal fusion and biologically informed attention mechanisms
• Personally tackle the hardest research problems, pushing the boundaries of what is possible in large-scale biomedical AI
• Establish architectural standards, validation practices and research patterns that guide the work of Staff and Senior AI Scientists
• Design and execute rigorous experiments that validate architectural hypotheses with downstream portfolio application in mind
• Partner closely with ML Engineers to ensure the most promising research prototypes can be optimised, scaled and productionised without loss of biological insight
• Collaborate with AI Reasoning to embed causality, interpretability and uncertainty considerations into architectural design
• Engage with Applied Analytics and AI to understand therapeutic needs to ensure architectures respect biomedical data complexity and structure and support fine-tuning and deployment for real-world impact
• Provide technical mentorship through design reviews, research discussions and publication guidance, raising the scientific quality bar across the team
• Publish and present research at top-tier venues, building external reputation and attracting exceptional scientific talent

Requirements

• PhD in AI, Computer Science, Mathematics, Physics, Computational Biology or a related field (or equivalent experience)
• Extensive experience in AI research with progression to senior technical leadership
• Deep expertise in foundation models, self-supervised learning and multi-modal architectures, preferably in the biomedical domain
• Proven track record of translating research into impactful applications
• Strong understanding of biological validation and drug discovery context
• Demonstrated ability to set research direction beyond individual projects
• Strong publication record at top venues with evidence of real-world or portfolio impact
• Experience mentoring researchers through technical leadership and scientific guidance
• Ability to communicate complex scientific concepts clearly across technical and non-technical audiences
• Comfortable representing the organisation externally through publications, presentations and collaborations