Senior Director, Head of AI for Clinical Development, Early BPRD

Competitive salary and benefits

Were building a connected end-to-end Enterprise AI engine - uniting data foundations AI technology process reinvention and business-facing AI to accelerate results across the whole value chain. Success depends on being exceptional connectors: youll actively leverage existing capabilities celebrate and promote reuse export breakthrough ideas across geographies and functions and obsess over scaling impact rather than building in isolation. If you thrive in high-collaboration environments where your role is to turn complex cross-functional problems into reusable enterprise-wide capabilities - and where the measure of success is adoption and scale not just innovation - youll have the platform (and sponsorship) to make it real.

About AISI

AI Science & Innovation (AISI) sits at the center of AstraZenecas R&D AI transformation. Our remit is to build buy and deliver the AI models and agents that change pipeline outcomes across discovery translational science biomarkers and clinical development.

Role Overview

AstraZeneca is building a world-class AI capability for Clinical Development within AISI to accelerate the design conduct and analysis of confirmatory trials across our Oncology and BioPharmaceuticals pipeline. We are hiring the Head of AI for Clinical Development Early BPRD to lead the science and the team that turns AI promise into real-world improvements in early phase clinical trials.

This is one of the highest impact challenges in AI for healthcare. The playbook for AI in Phase I/II trial design and decision-making will be developed in the next two to three years. We partner closely with domain experts in clinical development regulatory and biometrics to advance the science of clinical development to bring better treatments to patients faster while adhering to the highest evidentiary standards. Were hiring someone who sees that as the reason to come because they are committed to using AI for real measurable improvement in healthcare.

AI for clinical development is a field in motion. Foundation models multimodal learning agentic systems and causal AI advance rapidly and the regulatory and methodological frameworks around them are evolving in parallel. Youll pick the right bets among rapidly changing options and continuously absorb new methods as the field redefines whats possible. Comfort with ambiguity and an instinct to learn in public are core to the role.

The AI for Clinical Development function is being built from the ground up and youll help define how AstraZeneca does AI for early-phase trials. Expect an outsized voice with regulators scientific consortia and external partners during the narrow window when the rules of the road for AI in pivotal evidence are being written.

We hire for learning agility and technical excellence. The strongest candidate is the person who learns fast is comfortable with ambiguity prototypes early fails forward and partners credibly across communities (ML clinical biostatistics regulatory). Were seeking a scientist with the leadership technical depth and curiosity to develop adapt and apply the most advanced methods in AI including multimodal foundation models agentic AI generative patient models to support early phase clinical decision-making and who can sit across from clinical development teams to translate their priorities into actionable innovative and evaluable AI solutions.

Above all this is a role where the science matters. Every model you ship will eventually touch a trial that decides whether a patient gets a better therapy. That is the bar we hold ourselves to and the bar we hire to.

What youll do

• Lead AstraZenecas AI R&D for Phase I/II programs across BPRD leveraging and integrating AI solutions across the early development program leading a team of AI researchers and engineers.
• Develop and evaluate reusable AI methods for early phase trials e.g. innovative early phase trial design dose funding and optimization biomarker discovery digital twins/predictivemodeling for early phase decisions early efficacy and safety signal detection.
• Partner with the Early BPRD Clinical Development and Study Teams to embed AI and AI Strategy into study design and decision-making.
• Partner with Regulatory teams to develop AI-enabled development standards and evidence that meet regulatory and compliance requirements.
• Work closely with the Head of AI for Clinical Development Early Oncology and the Heads of AI for Clinical Development Late Oncology and BPRD to develop innovative and reusable strategies to guide early-to-late-phase decision-making and end-to-end evaluation strategies.
• Contribute to developing the AI for Clinical Development teams unified reusable and end-to-end strategies for AI method development evaluation monitoring and oversight.
• Contribute the AI evidence component to regulatory submission packages and the AI scientific and methodological voice on early-phase regulatory engagements.
• Represent AstraZeneca externally in industry forums scientific consortia and peer-reviewed venues.
• Serve as a thought partner for AISI and AI for Clinical Development leadership.
• Recruit mentor and lead a team of approximately five AI scientists and engineers as a player-coach who is hands-on with code models and submission-relevant analyses while building a high-performing team that keeps up-to-date with the latest advances in frontier AI models and agents.
  

Essential for the role

• Minimum degree requirements: PhD in Computer Science Machine Learning Computational Biomedical Sciences Biomedical Informatics Biostatistics or a closely related computational discipline with a strong hands-on computational track record. Alternatively MD (or equivalent clinical degree) with significant demonstrated hands-on and leadership experience in computer science/machine learning preferably with post-doctoral training or other advanced training in computer science informatics or data science.
• Minimum 8 years of combined experience across AI/ML method development and clinical development research with demonstrated impact on early phase trial design and/or decision-making.
• Strong knowledge Direct experience withof early phase trial design and conduct and the evidentiary bar that AI in pivotal evidence must clear for phase I/II decision-making.
• Strong softwareSoftware engineering skills: Python PyTorch Hugging Face cloud platforms (e.g. AWS Azure GCP) and modern LLM tooling.
• Peer-reviewed publications in top-tier conferences and/journals and shipped code inin clinical development clinical AI computational drug development and/or biomedical machine learning. Comfort writing code reviewing model implementations and reproducing results.
• Strong experience in generative and non-generative AI benchmarking and evaluation across clinical and/or biomedical settings.
• Deep familiarity with modern AI methods: foundation models (including clinical and multimodal) agentic systems generative patient models / digital twins longitudinal/time-series modelling causal inference predictive and prognostic modeling.
• Strong knowledge of early phase trial design and conduct and the evidentiary bar that AI in pivotal evidence must clear.
• Demonstrated track record of translating AI methods into applications that inform clinical and/or biomedical decisions including prospective evaluation deployment or contribution to submission-relevant evidence.
• Demonstrated scientific leadership: mentoring trainees leading multi-author projects and running a small team overseeing multiple projects.
• Excellent written and verbal communication able to translate technical findings for clinical regulatory and executive audiences.
  

Desirable for the role

• Direct industry experience in early-phase Oncology late-phase BPRD or confirmatory clinical development within a pharmaceutical or biotech R&D environment.
• Direct experience contributing to FDA EMA PMDA or MHRA submissions especially submissions involving AI/ML methods or innovative trial designs.
• Prior FDA EMA or PMDA engagement on AI methodology complex innovative trial Design or AI/ML qualification opinions.
• First- or last-author publications at top ML venues (NeurIPS ICML ICLR *CL) and/or top clinical and biomedical journals.
• Open-source contributions workshop organisation or standards-body participation.
  

When we put unexpected teams in the same room we ignite bold thinking with the power to inspire life-changing -person working gives us the platform we need to connect work at pace and challenge perceptions. Thats why we work on average a minimum of three days per week from the office. But that doesnt mean were not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

Why AstraZeneca:

Here technology and science meet to change whats possible for patients. You will join a company investing boldly in digital and data to become truly data-led where unexpected teams come together to address problems that have never been solved before. We empower engineers to experiment through hackathons and real-world pilots build at enterprise scale with modern platforms and learn continuously in a supportive high-standards culture that values kindness alongside ambition. Your contribution will unlock the potential of our science streamline how we work and help bring medicines to people faster.

Step into this role to design and ship AI systems that matterbring your expertise to Cambridge and help turn pioneering ideas into real-world impact today!

#EAI

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