We’re always seeking talented AI engineers and post-doctoral researchers to join our research team. If you are interested, please reach out! Females and underrepresented groups are particularly encouraged to apply.
Postdoctoral Fellow in Monitoring Clinical AI tools
This project aims to develop novel statistical and computational methods for monitoring 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.
Primary Responsibilities
- 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
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
AI engineer for the PROSPECT Team
Our team serves as the data science arm of the PROSPECT lab, which is the digital innovation team at Zuckerberg San Francisco General Hospital. The mission of PROSPECT is to improve health outcomes and equity in vulnerable and underserved populations through the application of novel technologies and digital tools. Our team is looking for an AI engineer to join our team, who will help research, architect, implement, and scale AI technologies at the hospital. The PROSPECT team is highly interdisciplinary, with experts spanning medicine, AI/ML, statistics, and clinical informatics.
Primary Responsibilities
Responsibilities include:
- Develop and deploy HIPAA compliant AI applications that integrate directly into the EHR system
- Build data pipelines that process high volumes of clinical notes and multi-modal Electronic Health Record (EHR) data
- Create robust infrastructure and tooling to enable and accelerate AI research efforts for the broader team
- Conduct independent research on how to ensure the safety, reliability, and effectiveness of clinical AI tools
- Collaborate closely with clinicians, informaticists, and interdisciplinary team members
- Prepare and submit research manuscripts to ML/AI conferences and/or clinical AI journals
- Design and implement open-source software packages for the research and clinical communities
Qualifications
The position requires an MS or PhD in computer science, data science, or a related field and/or equivalent working experience. We are looking for someone who:
- Has strong software engineering skills with experience building production systems
- Has experience with cloud platforms (AWS, Azure, or GCP) and containerization (e.g., Docker)
- Is proficient in designing databases, building scalable data pipelines, and processing large-scale datasets
- Can work independently and take ownership of complex technical projects
- Has experience with EHR systems and healthcare data integration (strongly preferred)
- Has experience with natural language processing and processing clinical notes (strongly preferred)
- Has interest in methodological development and independent research (strongly preferred)
Please submit the following materials to :
- A cover letter
- A CV summarizing your education and work experience so far
- The names and email addresses of three references
- A github repo of yours that you are most proud of
- One representative publication if applying for a research position
The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.