Postdoctoral Research Fellow

invites applications for a postdoctoral fellow position in the broad areas of statistics, data science, and artificial intelligence (AI). The position will focus on developing and applying novel statistical, machine-learning, and AI methods to advance biomedical and oncology research. The fellow will work under the supervision of Yi Li, with opportunities to collaborate with faculty in the Department of Biostatistics as well as medical and biomedical investigators at the University of Michigan and Harvard University. The position is funded by several NIH grants. The Department of Biostatistics is ranked No. 3 nationally by U.S. News & World Report. We are a thriving community of 47 faculty members, 16 postdoctoral fellows, 243 students, and 124 research and administrative staff, with strong ties to the Department of Statistics, the Medical School, the Michigan Institute for Data Science, and other research groups across the University of Michigan. The start date is flexible; the selected candidate will ideally begin as soon as possible. The postdoctoral fellow will work with Dr. Yi Li and his research group to develop innovative statistical and computational methods for large-scale, high-dimensional, and complex biomedical data. Research topics include but are not limited to modern survival analysis, high-dimensional statistical inference, AI and machine learning, deep learning and its statistical foundations, causal inference, statistical methods for medical imaging, precision medicine, statistical genomics, graphical models, and the analysis and integration of complex, high-dimensional biomedical data. The fellow will be expected to develop novel statistical methodology and apply it in real-world biomedical studies, prepare manuscripts for peer-reviewed journals, present and disseminate research findings, and collaborate with biomedical and clinical investigators. There will also be opportunities to contribute to the teaching of graduate courses. The successful candidate will receive a competitive salary, computing resources, and other benefits in accordance with departmental and university policies. PhD in Biostatistics, Statistics, Mathematics, Computer Science, or a related quantitative field by the time of appointment Strong methodological and computational skills Demonstrated interest or experience in health-related applications of statistical, data science, machine-learning, or AI methods Strong written and oral communication skills Ability to work collaboratively in interdisciplinary research teams Ann Arbor is a progressive city of approximately 118,000 year-round residents and approximately 43,000 students, with excellent schools and a wide variety of cultural, recreational, sporting, and musical activities. It consistently ranks highly in national surveys for quality of life and offers the amenities of a city many times its size. In addition to a career filled with purpose and opportunity, the University of Michigan offers a comprehensive benefits package to help employees stay well, protect themselves and their families, and plan for a secure future. This is a one-year appointment with the possibility of renewal for up to two additional years, contingent upon satisfactory performance and the availability of funding. The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third-party administrator to conduct background checks. Background checks are performed in compliance with the Fair Credit Reporting Act. Job openings are posted for a minimum of seven calendar days. The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled at any time after the minimum posting period has ended. The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.