Associate Principal Scientist, Immunology Cell Therapy Discovery

AI Expert, Immunology Cell Therapy Discovery

AstraZeneca, a global leader in biopharmaceuticals, is committed to discovering and delivering innovative therapies that transform patient outcomes. We are seeking a dedicated, hands‑on AI expert (Associate Principal Scientist or Principal Scientist level) to join our Immunology Cell Therapy Discovery team. This role will provide scientific and technical leadership across discovery initiatives with a dual emphasis on immune mediated diseases and computational innovation, with particular focus on bioinformatics, data science, and AI architecture to accelerate cell therapy discovery.

Serve as an AI Architect within the discovery organization, acting as an expert in AI‑enabled coding who can design, develop, and maintain reusable codebases that improve productivity, scalability, and scientific innovation. The role will lead innovation by integrating AI into core workflows, contribute to or build AI‑powered applications, and help drive transformation by advancing AI‑driven discovery. This includes architecting practical AI solutions for scientific workflows, enabling automation, improving knowledge extraction, and establishing sustainable coding and software practices that enhance research efficiency and impact.

Lead and apply advanced bioinformatics approaches to support research in immune mediated diseases. This includes the design and implementation of robust analytical workflows for bulk and single‑cell RNA sequencing, immune repertoire analysis, multi‑omics integration, target and pathway identification, and biomarker or endotype discovery. The role requires strong emphasis on reproducibility, data quality, statistical rigor, and the generation of actionable biological insights that inform experimental strategy and portfolio decisions.

Drive data science strategies that integrate complex biological datasets to improve understanding of disease heterogeneity, preclinical readout, and mechanism of action. The role will involve developing and applying statistical models, machine learning approaches, and advanced data integration methods to support hypothesis generation, patient segmentation, and evidence‑based decision‑making. The individual will also contribute to building scalable and interpretable analytical frameworks that connect computational findings with experimental validation.

• AI Architecture and Enablement:
  Design, develop, and maintain reusable AI‑enabled codebases and computational frameworks; integrate AI into core discovery workflows; contribute to or build AI‑powered applications; and advance the use of AI to improve scientific decision‑making and discovery efficiency.
• Bioinformatics and Computational Discovery:
  Design, implement, and continuously improve analytical workflows for bulk and single‑cell transcriptomics, immune repertoire analyses, multi‑omics integration, and biomarker/endotype discovery, ensuring reproducibility, quality control, and scientific rigor.
• Data Science Innovation:
  Apply advanced data science and machine learning methods to derive insights from high‑dimensional biological and translational datasets, supporting target selection, patient stratification, mechanism‑of‑action studies, and portfolio prioritization.
• Stakeholder Engagement:
  Build strong partnerships with key stakeholders internally and externally to align scientific, computational, and AI strategies with broader R&D priorities; communicate complex findings clearly to both technical and non‑technical audiences.

• Education and Industry
  
  Experience:
  
  PhD, MS, or BS with 5+ years of relevant biotech or biopharma industry experience in Immunology, Computational Biology, Bioinformatics, Molecular Biology, Cell Biology, Bioengineering, Data Science, Machine Learning or a related discipline.
• AI Architecture and Software Development:
  Proven ability as an AI‑enabled coder to design, develop, and maintain reusable codebases, contribute to or build AI‑powered applications, and integrate AI solutions into scientific workflows to improve efficiency and innovation.
• Programming…