AI Research Lead, AI for Oncology Clinical Development

Stack

Responsibilities

• ▹Co-own and evolve the AI strategy and roadmap for early and late-phase oncology clinical development
• ▹Serve as principal technical lead within matrixed teams, delivering complex, high-stakes AI programs on time
• ▹Evaluate and develop cutting-edge AI methods across problem framing, data readiness, governance, algorithm development, validation and deployment
• ▹Partner with clinical development, biometrics, regulatory and study teams to embed AI solutions
• ▹Design rigorous evaluation frameworks, benchmarking protocols and calibration plans
• ▹Build and maintain collaborations with academic groups, technology partners and industry consortia
• ▹Represent AstraZeneca at scientific conferences and author first- or last-author publications in leading ML and clinical AI journals
• ▹Mentor peers, deliver near-term wins and scale insights into reusable platforms and playbooks

Requirements

• ▹PhD in a quantitative discipline such as computer science, bioinformatics, computational biology, mathematics, physics, biophysics, computational neuroscience or biostatistics
• ▹2-5 years of work experience outside of PhD with measurable impact (e.g. models delivered, patents, SaMD filings, first-author publications, open-source projects, standards-body participation)
• ▹Exceptional software development and coding skills, leveraging frontier coding agent frameworks
• ▹Deep understanding of machine learning fundamentals, with domain expertise in one or more of: training and tuning foundation models, Bayesian inference, temporal modeling, multimodal integration and modeling, model calibration and domain adaptation, data-centric AI, model and data evaluations and benchmarking, model interpretability, model post-training and alignment

Nice to have

• ▹Deep expertise in cancer biology
• ▹Experience with biological data such as molecular (DNA, RNA, protein), imaging (radiology, microscopy) or clinical text (EHR, clinical notes)
• ▹Experience in drug development including clinical trial design, biomarker discovery, companion diagnostics, dosing, safety, endpoints and regulatory
• ▹Experience in a matrixed global organization spanning multiple sites and therapy areas
• ▹Proficiency in augmenting daily knowledge work with agentic tools
• ▹Up to date with the latest AI research and tools

Soft skills

What we offer

• ▹Working with clinicians, statisticians, engineers and product leaders in the same room
• ▹Modern tools and resources to back experimentation
• ▹Work that informs real decisions and influences pivotal studies

About the company

AstraZeneca is a company where digital and data are embedded across the full journey from discovery to the clinic, and where AI is used to make trials smarter, faster and kinder to patients.