Director of AI Research, AI for Oncology Clinical Development

What you'll do

• Set the AI strategy and roadmap for oncology early- and late-phase clinical development and lead complex AI projects.
• Develop, validate, and champion AI methods from problem definition through adoption, embedding solutions with clinical, biometrics, regulatory, and study teams.
• Build external collaborations, represent AstraZeneca in scientific forums and publications, establish best practices, and mentor junior scientists.

What they ask for

• PhD in a quantitative discipline, such as computer science, mathematics, physics, biophysics, bioinformatics, computational biology, computational neuroscience, or biostatistics.
• 4–8 years of work experience outside of a PhD, with measurable impact.
• Exceptional software development and coding skills, leveraging frontier coding agent frameworks.
• Deep understanding of machine learning fundamentals and domain expertise in at least one listed area, such as foundation models, Bayesian inference, temporal modeling, or multimodal modeling.

Nice to have

• Knowledge of biology and experience with biological data, drug development, or a matrixed global organization.
• Current knowledge of ML literature and connections to the ML community, such as publications, presentations, or collaborations.

Pay

$ 186.014,40 to $279.021,60 (USD, base salary)

Tools

frontier coding agent frameworks, machine learning, foundation models, Bayesian inference, temporal modeling, multimodal integration and modeling, multi-agent systems, agent harnesses

AI focus

Defines and delivers AI strategy and methods for oncology clinical development, including model development, evaluation, validation, and adoption to advance clinical studies and the drug pipeline.