AI Science & Engineering Analyst

Role: Scientist or Senior Scientist in AI/ML for Translational and Clinical Sciences, focusing on developing digital twins, foundation models, and multimodal clinical data integration to predict outcomes and discover biomarkers across AstraZeneca's therapeutic areas. Responsibilities include designing, training, and validating patient-level disease models, contributing to foundation model research, building clinical outcome prediction models, and developing scalable pipelines for multimodal data fusion. The role involves biomarker discovery, patient stratification, cross-functional collaboration with clinical, translational, and biometrics teams, and scientific leadership through publications and conferences. Requirements: PhD in a quantitative discipline (e.g., Computer Science, Biomedical Engineering) with experience in machine learning applied to biomedical data; proficiency in Python and modern ML frameworks; expertise in transformer architectures, longitudinal clinical data, and validation approaches; strong publication record; excellent communication skills. Senior level additionally requires 5+ years post-PhD experience, leadership in ML project delivery, and strategic influence. High-value biopharma specifics include focus on digital twin development, foundation models, multi-omics data integration, and regulatory considerations for AI/ML in healthcare. Collaboration spans Data Science, Clinical Development, Translational Medicine, and Biometrics, with an emphasis on scientific impact and regulatory compliance. Work setup is hybrid, based in the UK or US, with potential international collaboration.