Experteer Overview
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As part of the AI for Clinical Development team, you will develop and deploy AI/ML methods to inform clinical trial design and decision-making across early and late-phase programmes. You’ll lead end-to-end data science projects, partner with cross-functional teams, and build reusable data products that scale across geographies. Your work will shape trial design, biomarker strategy, and safety/efficacy evaluation within a high-regulatory context. You’ll operate at the frontier of foundation models and causal AI to drive real patient impact.
Compensaciones / Incentivos
• Develop, evaluate, and deploy reusable AI/ML methods for clinical trial settings (design support, dose optimisation, 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
• Partner with Clinical Development, Study Teams, Biometrics, and Regulatory to embed AI into study design and decision-making workflows
• Build reusable, well-documented data products (pipelines, packages, applications) with a software engineering mindset
• Apply cutting-edge methodologies (foundation models, agentic AI, generative patient models, longitudinal/time-series modelling, Bayesian/causal inference) with fit-for-purpose evaluation criteria




• Drive data-centric AI practices: curate high-quality datasets for training, evaluation, and benchmarking in clinical/regulatory settings
• Contribute to AI evaluation/benchmarking frameworks suitable for clinical/regulatory contexts
• Engage with internal data science communities and external scientific forums; contribute to publications and conferences
• Provide coaching and technical guidance to Senior Data Scientists and peers to promote best practices and scientific rigour
Responsabilidades
• PhD preferred; MSc with exceptional computational track record
• 2-5 years post-PhD (or equivalent) experience in AI/ML method development with impact in clinical/biomedical/drug xghoner development
• Deep experience with biological data (molecular, imaging, or clinical text)
• Deep technical expertise in foundation model training, Bayesian inference, longitudinal modelling, multimodal integration, data-centric AI, interpretability, and alignment
• Exceptional Python software development skills; experience with PyTorch and frontier agent frameworks; familiarity with cloud platforms (AWS, Azure, GCP)
• Proven ability translating complex methodologies into actionable insights and embedding solutions in cross-functional teams
• Excellent written and verbal communication for clinical, regulatory, and scientific audiences
Requisitos principales
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📌 Associate Director, Clinical AI (Barcelona)
🏢 AstraZeneca
📍 Barcelona