AI Researcher, Associate Director, AI for Clinical Development

AstraZeneca plc; Spain; On-site; EUR 90,000 - 130,000; Full time

Job summary

AstraZeneca plc in Barcelona, Spain, is seeking a Senior Scientist to lead hands‑on research and delivery of advanced AI models for clinical‑development decisions and workflows. This in‑office role requires a minimum of three days on‑site per week with no remote option.

You will work at the intersection of frontier AI, clinical trial methodology, and biomedical science, delivering robust AI-enabled solutions, evaluating models, and guiding strategy.

Qualifications

• Hold 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.

Responsibilities

• Own 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 evidence
• Build 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.
• Share your work through peer-reviewed publications, reusable tools, patents, scientific collaborations, and conference presentations where appropriate.
• 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 community

Skills

Python

PyTorch

JAX

TensorFlow

Unsupervised learning

Dimensionality reduction

Causal inference

Survival analysis

Longitudinal analysis

Bayesian modeling

Multimodal learning

Domain adaptation

Model interpretability

Education

MSc or PhD in Computer Science, Machine Learning, Biostatistics, Biomedical Informatics, Computational Biology, or related field

Tools

PyTorch

JAX

TensorFlow

Cloud computing

Job description

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 Overview

AstraZeneca 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.

We are looking for scientists who can move easily between a clinical question and the AI system needed to investigate it. 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. The common thread is rigor: understanding what the evidence shows, what it does not show, and what would need to be true before a result could influence a trial.

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 do not need to have worked with every new framework, but you should be curious, learn quickly, and have strong judgment about when a new approach is genuinely useful. 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.

Accountabilities

• Own 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 evidence
• Build 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.
• Share your work through peer-reviewed publications, reusable tools, patents, scientific collaborations, and conference presentations where appropriate.
• 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 community

Essential Skills/Experience

• Hold 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.
• Are comfortable working with AI agent harnesses, quick to pick up new approaches, and curious about what makes agents useful, reliable, and safe.
• Have strong Python and scientific-computing skills and experience with a modern ML framework such as PyTorch, JAX, or TensorFlow.
• Can explain technical findings, tradeoffs, and limitations to clinical, statistical, regulatory, engineering, and leadership audiences.

Essentials for the role

• Hold 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