Postdoctoral Fellow

Statistics Interest Group; San Francisco, Northern (CA, KY); Hybrid; USD 60,000 - 75,000; Full time

Job summary

University of California, San Francisco is seeking a Postdoctoral Fellow in the Department of Epidemiology and Biostatistics to advance statistical and computational methods for monitoring genAI-enabled medical devices. The role involves collaboration with FDA partners and UCSF’s genAI monitoring group, IMPACC, and aims to produce rigorous analyses and open-source software tools.

The ideal candidate holds a PhD in statistics/biostatistics/computer science/data science or a related field and has

Qualifications

• PhD in statistics, biostatistics, computer science, data science, or related field.
• Strong publication record.
• Strong computational background and ability to process large-scale multi-modal datasets.
• Preferably experience in sequential monitoring, changepoint detection, ML/AI, NLP.

Responsibilities

• Develop tools for monitoring genAI-enabled medical devices with rigorous statistical guarantees.
• Extract, process, and analyze multi-modal EHR data (e.g., clinical notes).
• Design and implement open-source software packages.
• Collaborate with interdisciplinary team.
• Prepare and submit research manuscripts to ML/AI conferences and statistics/clinical AI journals.

Skills

Publication track record

Computational proficiency

Methodological development

Independent research

ML/AI

NLP

Multi-modal data processing

Education

PhD in statistics/biostatistics/computer science/data science or related field

Job description

University of California, San Francisco – Postdoctoral Fellow

Company Name University of California, San Francisco

Position Title Postdoctoral Fellow

Company Information

This position is in the Department of Epidemiology and Biostatistics within the University of California, San Francisco (UCSF).

Duties and Responsibilities

We are looking for a postdoctoral fellow to join our project on developing novel statistical and computational methods to monitor generative AI-enabled devices, such as AI scribes. This project is a collaboration between the Feng lab, the FDA’s CDRH/OSEL/DIDSR team, and UCSF’s genAI monitoring group IMPACC.

• Develop tools for monitoring genAI-enabled medical devices, with rigorous statistical guarantees
• Extract, process, and analyze multi-modal Electronic Health Record (EHR) data (e.g., clinical notes)
• Design and implement open-source software packages
• Collaborate closely with interdisciplinary team
• Prepare and submit research manuscripts to ML/AI conferences, statistics journals, and/or clinical AI journals

Position Qualifications

The postdoctoral researcher position requires a PhD in statistics, biostatistics, computer science, data science, or a related field. We are looking for someone who:

• Has strong experience in methodological development and independent research, with a strong publication record
• Has a strong computational background and is comfortable processing large-scale, multi-modal datasets
• (Preferably) Has methodological expertise in one or more of: sequential monitoring, changepoint detection, ML/AI, natural language processing