"Post-Doctoral Fellowship for Contextualized Evaluation of AI for Healthcare"

The Heinz College of Information Systems and Public Policy at Carnegie Mellon University is seeking a postdoctoral researcher to advance the development of rigorous, clinically grounded evaluation methodologies for Artificial Intelligence (AI) in healthcare. Our research focuses on building comprehensive evaluation frameworks that consider the context of AI deployment within clinical workflows and its impact on downstream decisions and patient outcomes. The complexity of AI's integration into clinical workflows with human decision makers necessitates novel frameworks for evaluating AI models. We aim to address gaps in current AI evaluation practices by developing context-aware, decision-focused, and impact-driven methodologies. These include: benchmarks tailored to clinical use cases, evaluation approaches that account for human-AI interaction, and methods for assessing deployment readiness and clinical utility.

This work lies at the intersection of healthcare, AI/ML, and operations research (OR). This position offers an opportunity to contribute to research aimed at improving clinical and operational care delivery and patient safety through the development and evaluation of integrated AI/OR methods. Our research broadly explores the application of predictive, prescriptive, and generative AI techniques in various healthcare domains, including medication management and error reduction, clinical decision-making, and care coordination. Our existing collaboration network provides a rich environment for (1) identifying concrete use cases for AI evaluation methodologies and (2) validating the practical utility of our proposed approaches with clinical experts.

The postdoctoral researcher will play a central role in designing, implementing, and validating evaluation strategies that are both scientifically rigorous and practically useful. They will lead and contribute to the preparation of manuscripts for submission to top-tier journals in healthcare, AI/ML, and OR, and will play an active role in developing grant proposals for major funding agencies. A key goal is the design and development of deployable, scalable evaluation tools that can be adapted across a range of clinical contexts. The researcher will also have the opportunity to present their work at leading conferences and workshops, engaging with both academic and clinical communities to shape the conversation around trustworthy, real-world AI in healthcare.

The position will involve close collaboration with Professors Rema Padman and Holly Wiberg as well as external clinical collaborators. It offers an exciting opportunity to contribute to research that informs real-world AI adoption in healthcare-with the potential for high scholarly and real-world impact.

Ideal candidates will have significant AI/ML and optimization experience, leveraging both model-based and data driven approaches to decision making, and strong programming skills. We are seeking researchers who have a passion for applying these methods in healthcare and are committed to responsible model and methods development and deployment. Applicants should have received a Ph.D. within the last two years-or expected by September 2025-in Operations Research, Operations Management, Computer Science (AI/ML), Biomedical Informatics, or a related field. The award includes a competitive post-doctoral fellowship and up to $5000 for research-related travel expenses. The award is for a 12-month period.

Apply Now