Job Description
Are you ready to harness computational pathology and AI to move diagnostics from code to clinic? Do you want your work to directly shape how patients are diagnosed and treated? This role leads the scientific and technical integration of computational pathology and AI-enabled diagnostics into accredited laboratories, turning cutting-edge algorithms into validated tools that influence real clinical decisions. You will partner across research, clinical, regulatory, and lab operations to design fit-for-purpose studies, set rigorous acceptance criteria, and deliver analytical validation that stands up to regulatory scrutiny. Your leadership will ensure compliance, reproducibility, and documentation excellence, while your scientific curiosity drives new proposals in computational pathology and multimodal diagnostics that accelerate our pipeline and impact patient outcomes. Accountabilities:Developing and leading AI-based computational pathology diagnostic and integration within the AZ accredited labs, partnering across the organisation to ensure computational pathology diagnostics are accurately validated.Leading the scientific and technical diligence of AI-enabled diagnostic solutions for the clinical portfolio.Delivering innovative scientific proposals across core diagnostic areas, spanning computational pathology and multimodal diagnostics.Define fit-for-purpose study designs and acceptance criteria; lead analytical validation plans for AI algorithms to meet regulatory requirements; for example, in accordance with CAP/CLIA, GCP, and applicable IVD/Software as a Medical Device (SaMD) within our accredited labs.Maintain expert awareness of advances in computational pathology, including for example foundation models, multimodal AI, spatial biology, and evolving regulatory policy; evaluate and pilot new technologies with clear success criteria and build productive external collaborations and vendor relationships.Provide technical mentorship and matrix leadership with a focus on compliance, reproducibility, documentation excellence, and patient impact.
Responsibilities + Skills
Education
Masters/PhD or equivalent experience in a relevant field (e.g., Computational Pathology, Biomedical Engineering, Computer Science, Data Science, Bioinformatics).Hands-on experience deploying AI/computational diagnostics in regulated environments (e.g., CAP/CLIA, in alignment with IVD/SaMD expectations)Deep expertise in digital pathology and image analysis (e.g., whole-slide imaging, IHC/IF quantitation, tissue segmentation, cell phenotyping, computational biomarkers) and practical ML/AI model development and validation.Proven track record of validation and operationalization of AI diagnostic tools, including data pipeline design, MLOps in clinical settings, performance monitoring, bias/robustness assessment, and post-deployment lifecycle management.
Experience
