Senior Scientist - Clinical AI

About the role

AstraZeneca's BioPharma Clinical Development AI team, part of the AI Science & Innovation unit, is looking for a Senior Scientist to apply modern AI methods to the design, conduct and analysis of clinical trials. The role works in cross-functional teams across cardiovascular, renal, metabolic disease, respiratory and immunology, alongside data scientists and clinical collaborators. It is an in-office position in Barcelona with a minimum of three days per week on site, with no remote or travel flexibility.

Key responsibilities

• Develop and deploy AI/ML methods for clinical trials, including trial design support, dose optimisation, biomarker discovery, digital twins, predictive modelling and safety and efficacy signal detection.
• Contribute to end-to-end project delivery, from problem framing and methodology selection through validation and adoption, with guidance from senior colleagues on complex initiatives.
• Partner with Clinical Development, Biometrics and Regulatory colleagues to embed AI approaches into study design and decision-making.
• Build reusable, well-documented data products such as pipelines, packages and applications, with a software engineering mindset.
• Apply methods such as foundation models, agentic AI, generative patient models, longitudinal modelling, Bayesian inference and causal inference, with clear evaluation criteria.
• Practise data-centric AI and contribute to evaluation and benchmarking frameworks suitable for clinical and regulatory settings.
• Engage with internal and external scientific communities, contributing to publications and conference presentations.

Required profile

• Degree in a quantitative discipline (Computer Science, Machine Learning, Statistics, Mathematics, Biomedical Informatics, Computational Biology, Physics, Engineering) at Master's or PhD level, or equivalent experience.
• Demonstrated experience in AI/ML method development, shown through delivered models, publications, open-source contributions or applied projects, ideally in clinical, biomedical or drug development settings.
• Hands-on experience with biological or clinical data such as molecular (DNA, RNA, protein), imaging or clinical text (EHR, clinical notes).
• Nice to have: exposure to clinical development, MLOps/LLMOps, uncertainty quantification or clinical AI benchmarking, and peer-reviewed publications in clinical AI, computational drug development or machine learning.

Required skills

• Technical capability in one or more modern AI areas, such as foundation model training and fine-tuning, Bayesian inference, temporal and longitudinal modelling, multimodal integration, model interpretability or post-training and alignment.
• Strong Python skills, experience with PyTorch and modern LLM tooling, and familiarity with cloud platforms such as AWS, Azure or GCP.
• Excellent communication skills, able to explain complex methods to clinical, regulatory and scientific audiences.