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A postdoctoral research fellowship (up to 2 years) is available under the direction of Ashkan Ertefaie, PhD (Associate Professor of Biostatistics, University of Rochester) and Michael McDermott, PhD (Professor of Biostatistics, University of Rochester). This position is supported by an NIH-funded grant focused on constructing optimal treatment strategies for patients with Parkinson's disease using a harmonized dataset. The Fellow will have access to an unprecedented, harmonized dataset stored at the Department of Biostatistics and Computational Biology. The harmonized data include longitudinal measurements of patients’ clinical profiles, treatment history, and demographics that provide an excellent opportunity to construct data-driven treatment strategies. The Fellow will receive dedicated mentorship, with the expectation that their time as a Fellow will advance their career development. The expectation is that the duration of this position will be two years, and is intended to prepare the Fellow for successful placement in an academic tenure-track appointment at a major research university. Alternatively, it can provide a candidate who has deferred an appointment with an opportunity to engage and collaborate with faculty on high-quality research projects prior to starting their permanent position.

A major focus of this postdoctoral research fellowship will be on a National Institute of Neurological Disorders and Stroke-funded study entitled “Advancing personalized medicine in Parkinson's disease using harmonized multi-site clinical data”. The proposal expands the scope of existing methods in developing treatment strategies by relaxing certain unrealistic assumptions and through the use of flexible modeling techniques while maintaining valid statistical inference.

The candidate must hold a doctoral degree in a quantitative field, such as statistics, biostatistics, or computer science. Preference will be given to candidates with research experience in some of the following areas: (1) precision medicine, (2) causal inference methodology, (3) longitudinal data, and (4) machine learning. Candidates with strong computational skills (proficient in one of the programming languages, C/C++, Python, and R) are especially encouraged to apply. The University of Rochester is an Affirmative Action, Equal Opportunity Institution. Women and minority candidates are strongly encouraged to apply.