Associate Director role leading AI research and engineering for oncology clinical development. The position focuses on designing and deploying machine learning solutions to improve trial efficiency, patient outcomes, and decision-making across late-stage oncology programs.
Responsibilities
- Co-own and evolve AI strategy for early and late-phase oncology clinical development, prioritizing high-impact opportunities
- Serve as principal technical lead for complex AI programs, ensuring scientific rigor and regulatory compliance
- Partner with clinical, biometrics, and regulatory teams to integrate AI solutions into study design and portfolio decisions
- Design evaluation frameworks and validation protocols to ensure model reliability and real-world clinical applicability
- Build collaborations with academic and technology partners; publish research in ML and clinical AI journals





Requirements
- PhD in quantitative discipline (computer science, bioinformatics, computational biology, mathematics, physics, biostatistics, or related field)
- 2-5 years post-PhD work experience with demonstrated impact in AI/ML delivery or research
- Advanced software development and coding proficiency with modern ML frameworks
- Deep machine learning expertise in areas such as foundation models, Bayesian inference, temporal modeling, or model interpretability
- Experience with biological data types: molecular, imaging, or clinical text data
- Familiarity with drug development including clinical trial design, biomarkers, dosing, or regulatory pathways

📌 AI Research Lead, AI for Oncology Clinical Development (España)
🏢 AstraZeneca
📍 España