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

We're 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: you'll 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 - you'll have the platform (and sponsorship) to make it real. 

About AISI

AI Science & Innovation (AISI) sits at the center of AstraZeneca’s 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 Oncology 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. We’re 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. You’ll pick the right bets among rapidly changing options, and continuously absorb new methods as the field redefines what’s 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 you’ll 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). We’re 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 you'll do 

• Lead AstraZeneca’s AI R&D for Phase I/II programs across Oncology, 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 Oncology 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 BPRD 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 team’s 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 5+ 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. 
   

Office Working Requirements 

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

The annual base pay for this position ranges from $ 203 213,60 - 304 820,40 Annual USD. Base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition, our positions offer a short-term incentive bonus opportunity; eligibility to participate in our equity-based long-term incentive program. Benefits offered include a qualified retirement program [401(k) plan]; paid vacation and holidays; paid leaves; and, health benefits including medical, prescription drug, dental, and vision coverage in accordance with the terms and conditions of the applicable plans. 

#EAI

  

Date Posted

02-juni-2026

Closing Date

16-juni-2026

Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.