The Fries Lab at Stanford University is seeking multiple postdoctoral scholars to join their team in Palo Alto, CA. The lab focuses on developing and evaluating healthcare foundation models that learn from longitudinal electronic health records (EHRs), clinical text, and multimodal data. 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 machine learning or medical AI venues. Interest in real-world clinical data, mentorship, and collaboration with students and clinicians is essential.

The position offers a competitive salary and benefits, visa sponsorship, access to large-scale GPU resources (B200, H100, A100, L40S), and massive longitudinal datasets (~4 million patients, including notes and imaging). The start date is flexible for Summer–Fall 2026, and applications are reviewed on a rolling basis.

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. For more information, visit the Fries Lab academic page.