The post-doctoral candidate will collaborate with a team led by Dr. Liangyuan Hu on projects funded by the NIH and PCORI developing Bayesian machine learning methods for causal inference with complex time-to-event data. This position also provides the opportunity to engage in a multi-institutional collaboration, aimed at both the development of statistical methodologies and novel applications to cancer, cardiovascular disease and Covid-19 research. The multi-institutional collaboration spans across Brown University, Rutgers University and Icahn School of Medicine at Mount Sinai (ISMMS). We seek candidates who work in the areas of causal inference, Bayesian inference, machine learning and prediction and methodology for electronic health records data.
Applicants should have a PhD in Statistics, Biostatistics, Data Science, Epidemiology, Computer Science or related area. Strong statistical knowledge in causal inference and computational and programming skills (R/Python and/or C++) are required. Successful candidates will have strong communication skills (written and oral). The ISMMS values diversity and inclusion as essential to achieving excellence.
About Icahn School of Medicine at Mount Sinai Hospital
The Institute of Healthcare Delivery Science (I-HDS)) is an innovative and trans-disciplinary research institute associated with the Department of Population Health Science and Policy at the Icahn School of Medicine at Mount Sinai. Its mission is to develop, analyze, and disseminate clinical evidence toward improvements in the quality, safety, outcomes and efficiency of care delivered in the Mount Sinai Health System, an integrated health care system now encompassing seven hospitals within New York City.
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