Postdoctoral fellow for clinical AI monitoring

We’re seeking talented post-doctoral researchers to join our interdisciplinary research team on an ambitious multi-year mission to develop cutting-edge computational tools for monitoring, diagnosing, and updating ML/AI algorithms. The goal is to ultimately rigorously test and deploy these tools in multiple hospital systems. If this opportunity excites you, please see below! The team is led by Drs. Jean Feng and Suchi Saria. Other team members include faculty across UCSF, JHU, and Northwell with expertise in ML/AI/statistics and medicine, including Fan Xia, Julian Hong, Lucas Zier, Arjun Sondhi, and more!

The postdoctoral position (100% funded) will be for two years, with potential for continuation. Salary and benefits are competitive.

Primary responsibilities:

• Develop tools for monitoring, diagnosing, and updating ML/AI systems in real-world clinical settings with rigorous statistical guarantees. See example papers from our group here, here, here, here, and here.
• Design and implement robust, scalable software libraries and data pipelines
• Collaborate with deployment teams to ensure developed tools work well in real-world settings
• Prepare and submit research manuscripts and technical reports

Qualifications:

The post-doctoral researcher position requires at least a PhD degree in computer science, (bio)statistics, data science, or related fields. We are looking for someone who:

• has experience in methodological development and can perform independent research, with a strong and relevant publication record
• (preferably) has experience in at least one of these fields: sequential monitoring, multiple hypothesis testing, machine learning, causal inference, post-prediction inference
• is comfortable working with large datasets as well as data from different modalities (tabular, imaging, text)
• is able to work collaboratively with a team