Faculty - Department of Biomedical Informatics, Division of Biostatistics and Population Health, Biostatistics (Open Rank Tenure-Track)

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Job Title:

Faculty - Department of Biomedical Informatics, Division of Biostatistics and Population Health, Biostatistics (Open Rank Tenure-Track)

Department:

Medicine | School Biomed Sci - Biomedical Informatics

Tenure faculty (regardless of rank) - persons with the titles of professor, associate professor, assistant professor and instructor who serve on appointments totaling 50% or more service to the university and who are eligible for tenure or who have obtained tenure. Duties and responsibilities are assigned in accordance with the workload guidelines laid out in the pattern of administration of each faculty member’s tenure initiation unit (TIU) and, as appropriate, regional campus; obligations will include research, service and/or teaching or clinical practice.  These faculty will have earned doctorate or other terminal degree in the relevant field of study or possession of equivalent experience.

Division of Biostatistics and Population Health (BPH, https://medicine.osu.edu/departments/biomedical-informatics/divisions/division-of-biostatistics-and-population-health) in the Department of Biomedical Informatics (BMI, http://bmi.osu.edu) and Center for Biostatistics (CFB, https://medicine.osu.edu/departments/biostatistics) at The Ohio State University (OSU) is currently seeking applicants for open rank tenure-track faculty in biostatistics. Academic rank and track commensurate with academic record and experience.

Position Overview

Candidates with expertise and interests in clinical trial, population health science, Bayesian statistics, epidemiology, causal inference, statistical learning, artificial intelligence (AI), high-dimensional data, and/or electronic medical records are encouraged to apply. Successful applicants should have a Ph.D. in Statistics, Biostatistics, Epidemiology or a related discipline, with scientific collaboration and research interests in one or more of the following areas:

• Clinical trials, including Bayesian designs, pragmatic trials, hybrid-type studies, clustered designs, de-centralized trials, and rapid cycle research to support learning health systems.
• Clinical trial data management, including data coordination center (DCC) operations, database development, quality assurance, and collaboration on multi-center clinical trials.
• High-dimensional data, including complex correlated structures, novel omic data platforms, , statistical methods in AI/ML, and methodolog