Jason Alan Fries

Assistant professor developing foundation models for longitudinal healthcare data.

Join Us

Hiring for 3 roles

🧪 Data-Centric AI Postdoc
🤝 Human-AI Teaming Postdoc
🛠️ ML Engineer (Staff)

Why Stanford?

The successful candidate will have access to:

GPU cluster access (B200, H100, L40S, A100)
Longitudinal EHR data from over 4.3 million patients, including structured data and clinical notes
CT and radiology data, and other medical imaging datasets
Collaborations across Stanford Medicine, Computer Science, Biomedical Data Science, and clinical departments
Opportunities to mentor students, publish in top ML venues, and help shape emerging directions in healthcare AI

🧪 Postdoctoral Scholar – Data-Centric AI for Healthcare (Fall 2026)

The Fries Lab at Stanford University is seeking a postdoctoral scholar to help develop the next generation of data-centric AI methods for healthcare.

Research Directions

This position is part of a new NIH-funded effort, in collaboration with the Shah Lab, focused on adapting foundation models to electronic health records and other clinical data sources. Areas of interest include:

Synthetic data generation for machine learning
Data valuation, curation, and filtering
Post-training and alignment of foundation models
Longitudinal patient modeling and temporal reasoning
Learning from multimodal healthcare data (coded data, continuous labs, clinical notes)
Evaluation and benchmarking of clinical AI systems
Efficient and long-context machine learning methods

Example Papers

Recent work from the lab includes:

TIMER — Temporal reasoning benchmarks and methods for understanding longitudinal patient timelines (npj Digital Medicine).
MedHELM — Holistic evaluation of large language models for medical tasks with MedHELM (Nature Medicine).
MedAlign — A benchmark and dataset for instruction-following on electronic health records grounded in real patient data (AAAI 2024).

Qualifications

Applicants should hold a PhD in Computer Science, Machine Learning, Statistics, Biomedical Informatics, or a related field and have a strong record of research accomplishments.

How to Apply

Email your application to jfries@stanford.edu.

Subject line: Postdoc Application 2026 – Fries Lab

Please include your (1) latest CV; (2) research statement; and (3) contact information for three references.

🧪 Postdoctoral Scholar – Human-AI Collaboration for Healthcare (Fall 2026)

The Fries Lab at Stanford University is seeking a postdoctoral scholar to develop AI systems for complex clinical decision-making, with a focus on multimodal foundation models, human-AI collaboration, and agentic systems.

Research Directions

This position will contribute to Stanford's ARPA-H-supported effort to develop AI-assisted tumor boards and multimodal foundation models for cancer care:

https://dbds.stanford.edu/dbds-awarded-8-9-million-from-arpa-h-for-ai-tumor-board-research/

and Weill Cancer Hub West:

https://med.stanford.edu/cancer/research/weill-cancer-hub-west.html

Research focuses on developing AI systems that help clinicians interact with multimodal patient data, construct clinical knowledge bases, define patient cohorts, and support complex cancer care decisions.

Areas of interest include:

Human-AI collaboration for clinical decision-making
Agentic workflows for evidence synthesis, cohort definition, and population-scale chart abstraction
AI-assisted multidisciplinary tumor boards
Clinical knowledge base construction
Foundation model post-training (SFT, RL, preference optimization)