Postdoctoral Research Scientist

Postdoctoral Research Scientist – Columbia University Irving Medical Center

Overview

A Postdoctoral Research Scientist position is immediately available in the Department of Biomedical Informatics (DBMI) at the Columbia University Irving Medical Center. We are seeking a highly motivated researcher with a strong background in machine learning to conduct cutting‑edge research developing new methods and foundational understanding of generalization, transfer learning and/or domain adaptation for healthcare applications. The candidate will carry out research in the labs of PIs Shalmali Joshi and Noémie Elhadad.

Researchers at the DBMI have access to 6.5 million longitudinal full patient records and large national claims datasets and have the opportunity to deploy their research into the healthcare ecosystem at the Columbia University Irving Medical Center and New York‑Presbyterian Hospital. Columbia DBMI also serves as the coordinating center for OHDSI, the open‑science observational health data science and informatics initiative. If you are interested in high‑quality methodological work with strong potential for real health impact, this is the right place for you.

The Postdoctoral Research Scientist will conceptualize and lead projects addressing major challenges in the area of generalization relevant to healthcare. The researcher will develop principled methods using causal inference, probabilistic modeling and deep learning in static and longitudinal settings, and will have the opportunity to apply novel methodological work on psychiatry and mental health data combining multiple data sources and heterogeneous data types.

• Ph.D. in machine learning, statistics, or an equivalent field.

• Strong research interest in machine learning for health and medicine, with a relevant publication record (ICML, NeurIPS, AISTATS, UAI, MLHC, CHIL, JAMIA, KDD, etc.).
• Experience working with Electronic Health Record data and combining multiple data domains is a plus.
• Relevant research background in causal inference, probabilistic modeling, and generalization in ML, as well as modeling longitudinal data, is a significant plus.

Please use the following link to apply:  Application .