Postdoctoral Research Scientist

The Department of Epidemiology at Columbia University Mailman School of Public Health in New York City invites applications for a Postdoctoral Research Scientist. Dr. Miles and Dr. Rudolph are looking for a postdoctoral researcher who is interested in developing semiparametric methodology for causal inference, particularly on the topics of transportability and generalizability, applying these methods to drug abuse trial data, and developing software to disseminate these methods. The postdoctoral research scientist will work on cutting-edge research projects, and will collaborate with a multidisciplinary team of statisticians, epidemiologists, programmers, and clinicians specializing in addiction to design, develop, implement, and disseminate innovative tools for causal inference. Current projects include (but are not limited to): developing semiparametric efficient methodology for efficiently combining data across multiple studies, developing methodologies for studying effect heterogeneity, estimating optimal individual treatment rules, and conducting sensitivity analyses in such settings, and developing statistical software to disseminate these methods. While participating in these projects, the individual will be actively involved in the Causal Inference Learning Group and departmental activities, and will be provided with the opportunity to pursue their research agenda in an intellectually vibrant environment with active mentorship.

Key Responsibilities:

* Conduct high-quality research in developing causal inference and semiparametric methodology with applications in drug abuse research, resulting in publications in top-tier journals and conferences.

* Collaborate with an interdisciplinary team to understand public health challenges and develop causally-sound solutions.

* Participate in the development and submission of research proposals to secure external funding.

* Present findings at national and international conferences and contribute to the scientific community.

* A Ph.D. in biostatistics, statistics, computer science, epidemiology, data science, economics, or a related field, with a strong focus on causal inference and/or semiparametric inference.

* Demonstrated experience in causal inference and/or semiparametric inference research, as evidenced by published papers or projects.

* Proficiency in the R programming language and experience with developing R packages.

* Excellent analytical, problem-solving, and communication skills.

* Knowledge of advanced statistical techniques and their application in public health research.