Post Doctoral Fellow-MSH-76880-012

Mount Sinai Health System•New York, NY

9h•Onsite

About The Position

The Suarez-Farinas Lab at the Icahn School of Medicine at Mount Sinai is seeking a highly motivated postdoctoral fellow to work at the intersection of artificial intelligence, causal inference, and translational health data science. Our research focuses on developing rigorous statistical and machine learning methods to uncover disease mechanisms, identify treatment-response biomarkers, and advance precision medicine using clinical trials, real-world data, and multi-omics datasets. A central focus of the lab is moving beyond purely predictive models toward causal, mechanistic, and clinically actionable insights, while building scalable and reproducible analytical pipelines. The postdoctoral researcher will lead and contribute to cutting-edge projects involving AI and data science in healthcare. This is a full-time, on-site position based in New York, United States.

Requirements

PhD in statistics, biostatistics, computer science, data science, bioinformatics, or a related quantitative field
Strong background in ML and interest or experience in causal inference (e.g., causal ML, treatment effect estimation)
Proficiency in R and/or Python, with experience handling large, complex datasets
Solid understanding of statistical modeling, experimental design, and algorithm development
Demonstrated ability to work independently and collaboratively in a multidisciplinary environment
Strong written and oral communication skills