This is an in-office role based in Barcelona, ES, with a requirement to work a minimum of three days per week on-site. Remote or travel flexibility is not available.
Role OverviewAstraZeneca is building a world-class AI capability for clinical development within AISI to accelerate the design, conduct, and analysis of clinical trials across our Oncology and BioPharmaceuticals pipeline. We are hiring a Senior Scientist to lead hands-on research and technical delivery of advanced AI models and agentic systems for clinical-development decisions and workflows.
You might be developing a new method for analyzing randomized clinical trials, testing a multimodal model, or building an agent that can carry out a reproducible scientific workflow. AI for clinical development is changing quickly. Foundation models, multimodal learning, agentic systems, post-training methods, and evaluation science are evolving alongside regulatory expectations. You will work at the intersection of frontier AI, clinical trial methodology, and biomedical science. You will work at the intersection of frontier AI, clinical trial methodology, and biomedical science. Your research may address treatment-effect heterogeneity, predictive biomarker discovery and validation, patient stratification, time-to-event outcomes, cross-trial generalization, and other problems that shape clinical-development decisions. Your work will also help establish how advanced AI systems are evaluated, governed, and used responsibly in the development of new medicines.
AccountabilitiesOwn the end-to-end scientific and technical delivery of one or more clinical AI workstreams, from problem definition and data assessment through prototyping, validation, translation, and iteration.
Adapt and apply emerging AI methods to clinical-development problems, investigate failure modes,



and make clear recommendations based on the evidenceBuild and evaluate agentic AI systems for clinical-development use cases, including retrieval, tool use, code execution, memory, multi-step workflows, and human oversight.
Write high-quality Python and build reproducible research workflows using modern ML frameworks, version control, testing, and cloud or high-performance computing environments.
Act as a senior scientific and technical partner across the organization, influencing clinical strategy, evaluation approaches, platform capabilities, and investment decisions.
Build the research culture of the team through scientific review, constructive challenge, and mentorship of scientists and engineers. Represent AstraZeneca with external partners, scientific consortia, regulators, and the research communityEssential Skills/ExperienceHold an MSc or PhD in Computer Science, Machine Learning, Biostatistics, Biomedical Informatics, Computational Biology, or a closely related quantitative field, or have a BSc with substantial equivalent experience.
Have independently delivered a meaningful AI or ML research project, workstream, model, evaluation, or software capability from initial question through a clear and reproducible result. Have a record of strong research or technical contributions, such as peer-reviewed work, validated models, reusable software, datasets, benchmarks, patents, or deployed capabilities.



Bring expertise in relevant research topics, such as unsupervised learning, dimensionality reduction, causal inference, survival or longitudinal analysis, Bayesian modeling, multimodal learning, domain adaptation, model interpretability. Have strong Python and scientific-computing skills and experience with a modern ML framework such as PyTorch, JAX, or TensorFlow. Essentials for the roleHold an MSc or PhD in Computer Science, Machine Learning, Biostatistics, Biomedical Informatics, Computational Biology, or a closely related quantitative field, or have a BSc with substantial equivalent experience.
Have independently delivered a meaningful AI or ML research project, workstream, model, evaluation, or software capability from initial question through a clear and reproducible result.
Have a record of strong research or technical contributions, such as peer-reviewed work, validated models, reusable software, datasets, benchmarks, patents, or deployed capabilities.
Bring expertise in relevant research topics, such as unsupervised learning, dimensionality reduction, causal inference, survival or longitudinal analysis, Bayesian modeling, multimodal learning, domain adaptation, model interpretability.
Have strong Python and scientific-computing skills and experience with a modern ML framework such as PyTorch, JAX, or TensorFlow.
Desirables for the roleExperience with multimodal biomedical data such as clinical text, EHR or trial data, biomedical imaging, genomics, transcriptomics, spatial biology, or real-world data.
Hands-on experience with large language models or agentic systems, including fine-tuning or post-training, retrieval-augmented generation, tool use, agent harnesses, multi-step orc

📌 AI Researcher, Associate Director, AI for Clinical Development (España)
🏢 AstraZeneca
📍 España