/or electronic health-record data. Implement model evaluation frameworks covering performance, calibration, robustness, bias, uncertainty, and clinically relevant endpoints. Support prospective and retrospective validation of AI systems in clinical environments. Collaborate with clinicians and domain experts to assess clinical utility, workflow integration, and safety. Develop production-quality software … models into healthcare systems. Monitor deployed models for performance degradation, data drift, safety issues, and unexpected behaviour. Maintain appropriate documentation covering datasets, model development, validation, limitations, intended use, and risk controls. Contribute to clinical AI governance, risk management, and regulatory submissions where required. Communicate technical findings clearly to both technical ...