Postdoctoral Positions in Healthcare AI, Multimodal Foundation Models, and Biomedical Data Science at Stanford University

The Fries Lab at Stanford University, led by Assistant Professor Jason Fries, is recruiting multiple postdoctoral scholars to advance research in healthcare AI, multimodal foundation models, and biomedical data science. The lab focuses on developing and evaluating healthcare foundation models that learn from longitudinal electronic health records (EHRs), clinical text, and multimodal data. Key research themes include multimodal and longitudinal foundation models, benchmarking and evaluation for healthcare AI, multimodal medical reasoning, patient representation learning, data-centric AI, synthetic data generation, and human-AI teaming. Application areas span oncology, precision medicine, and pediatrics. Applicants should have a PhD in a machine learning-related field such as computer science, data science, or informatics, with a strong research background and publications in top ML or medical AI venues. Interest in real-world clinical data and enthusiasm for mentorship and collaboration with students and clinicians are essential. The position offers a competitive salary and benefits, visa sponsorship, access to large-scale GPUs (B200, H100, A100, L40S), and massive longitudinal datasets (~4 million patients, including notes and imaging). To apply, candidates should email their application materials to [email protected] with the subject line 'Postdoc Application 2026 – Fries Lab.' Required materials include a research statement (up to 3 pages), CV, and 3 references. The start date is flexible for Summer–Fall 2026, and applications are reviewed on a rolling basis. The position is based in Palo Alto, California. For more information, visit the Fries Lab academic page or contact Professor Jason Fries directly.