You will lead high-stakes AI projects with scientific authority, shaping enterprise-grade methods and regulatory-aligned solutions. Lead complex AI projects through problem definition, methodology selection, validation, regulatory alignment, and enterprise adoption Develop and govern reusable enterprise-grade AI methods for clinical trials (design support, dose optimization, biomarker discovery, digital twins, predictive modelling, safety/efficacy signals) Champion data-centric AI practices at programme level: data acquisition, curation,



quality control for training and evaluation mentor junior scientists to promote rigor and reuse Requisitos principales PhD in a quantitative discipline with hands-on computational track record 4–8 years post-PhD in AI/ML method development with impact in clinical/biomedical settings Deep experience with biology and biological data (molecular, imaging, or clinical text) Expertise in modern AI methods (foundation models, Bayesian inference, temporal modelling, multimodal integration, domain adaptation, interpretability) Exceptional software engineering skills (Python, PyTorch, frontier agent frameworks, LLM tooling, cloud platforms) Foundation model training and fine-tuning Temporal/longitudinal modelling

📌 Director, Data Scientist - Clinical AI (Barcelona)
🏢 AstraZeneca
📍 Barcelona