Assistant Professor; Tenure Track

University of Rochester – Assistant Professor (Tenure Track) Company Name University of Rochester Position Title Assistant Professor (Tenure Track) Company Information

The Department of Biostatistics & Computational Biology (DBCB), located on the Health Sciences Campus, currently has 20 faculty members with methodological research interests collectively spanning a broad cross-section of topics in biostatistics and statistics; examples include clinical trial design (including adaptive and SMART trials), causal inference, longitudinal data, survival analysis, Bayesian methods, analysis of social and biological network data, systems biology, and the analysis of large-scale data sets (e.g., from high-throughput genome sequencing and imaging applications).

DBCB faculty also collaborate with over 30 departments and centers, including the Departments of Biomedical Genetics, Medicine, Neurology, Pediatrics and Psychiatry; the Eastman Institute for Oral Health; the NCI-designated Wilmot Cancer Institute; the Center for Health + Technology; the Environmental Health Sciences Center; the Genomics Research Center; and, the Clinical and Cardiovascular Research Center. These collaborations provide a rich source of data and pose novel methodological challenges.

Many faculty hold joint appointments in the departments or centers in which they collaborate. The Department offers a highly regarded PhD program in Statistics; it also runs two master’s degree programs. Many graduates of these programs have gone on to distinguished careers in academia or industry. The DBCB also supports several postdoctoral fellows, master’s-level statisticians and programmers.

The Department of Biostatistics and Computational Biology (DBCB) at the University of Rochester (UR) is seeking highly qualified applicants for a tenure-track assistant professor position. The DBCB has a strong preference for attracting applicants with dual interests in the development of statistical/computational methodology and collaborative biomedical research; successful candidates will possess the research skills and experience required to become leaders in both dimensions.

Although applications are welcomed from all corners of biostatistics and will be reviewed carefully, ideal candidates will have expertise and interests in: clinical trial design, including Bayesian adaptive design; gene-trait association studies; omics-informed precision medicine; spatial transcriptomics and/or functional genomics. Each of these areas offers strong opportunities for collaboration with faculty across the UR Medicine health system, and either aligns with or complements departmental strengths.

Training or expertise in related areas such as casual inference, Bayesian inference, high-dimensional data analysis, machine learning, data integration and data visualization are highly desirable.

Doctoral degree in biostatistics, statistics, or a strongly related discipline with equivalent training. In addition to strong potential for research, successful candidates will have excellent oral and written communication skills and high enthusiasm for graduate teaching and advising.