Experteer Overview

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Join AstraZeneca’s AI for Clinical Development team to advance AI methods that inform trial design, dose optimization, and safety evaluation across early and late phase programmes. You will work with cross-functional teams across cardiovascular, renal, metabolic, respiratory, and immunology areas to scale reusable AI solutions that improve pipeline outcomes. This is a hands-on, frontier role shaping methods such as foundation models and causal AI with strong regulatory alignment.

You will lead data-driven projects that directly impact patient therapies and trial decisions.

Compensaciones / Ventajas

- Develop, evaluate, and deploy reusable AI/ML methods for clinical trial settings (design support, biomarker discovery, digital twins, predictive modelling, safety/efficacy signals)
- Lead end-to-end delivery of data science projects from framing to adoption in study teams
- Collaborate with Clinical Development, Study Teams, Biometrics, and Regulatory to embed AI strategies into study design
- Build reusable data products (pipelines, packages, applications) with a software engineering mindset
- Apply advanced methodologies (foundation models, agentic AI, longitudinal modelling, Bayesian/causal inference) with clear evaluation criteria




- Drive data-centric AI practices: curate datasets, ensure quality, benchmarking for clinical/regulatory settings
- Contribute to AI evaluation/benchmarking frameworks for clinical contexts
- Engage with internal data science communities and external forums; contribute to publications
- Provide coaching to Senior Data Scientists and peers to promote best practices and rigour

Responsabilidades

- PhD preferred; MSc with exceptional computational track record considered
- 2–5 years post-PhD (or equivalent) AI/ML method development with demonstrated impact in clinical/biomedical settings
- Deep knowledge of biology with hands-on experience with biological data xugodme (molecular, imaging, clinical text)
- Expertise in modern AI methods: foundation model training, Bayesian inference, longitudinal modelling, multimodal integration, data-centric AI, interpretability, alignment
- Excellent software development in Python; experience with PyTorch and LLM tooling
- Experience building/deploying robust, reusable analytical solutions; familiarity with cloud platforms (AWS, Azure, GCP)
- Track record translating complex methods into actionable insights within cross-functional teams
- Strong written and verbal communication skills for clinical, regulatory, and scientific audiences

Requisitos principales

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📌 Associate Director, Clinical AI (Barcelona)
🏢 AstraZeneca
📍 Barcelona