Description



The University of Chicago's Department of Human Genetics is searching for Research Assistant Professors to participate in statistical and computational research related to human genetics as part of the Program for Computational Biology. The primary activity of the appointees will be to conduct academic research in association with a faculty member or a team that includes biologists and statisticians. Appointees may also participate in educational activities at the interface of computation and biology, such as teaching computational methods relevant to biology in bootcamp format. The appointees will complement existing areas of strength and contribute to project conception and execution, as well as software development. We are particularly interested in candidates with experience developing and/or applying methods for genetic association analysis, population genetics, and single cell genomics. Experience with cluster and/or cloud computing will also be helpful. Compensation (including a generous package of fringe benefits) is dependent upon qualifications.


Applicants must have: 1) a doctoral degree or equivalent in computational biology, statistics, computer science or related discipline, and 2) completed postdoctoral training prior to the start of employment. Assessment of applications will consider experience in developing and applying statistical methods to genetic and genomic problems, and with working as part of a collaborative team, as well as technical expertise in statistical methods, computational methods, and software development.


To be considered, those interested must apply through The University of Chicago's Academic Recruitment job board, which uses Interfolio to accept applications: http://apply.interfolio.com/124026. Applicants must upload: a CV including bibliography, a research statement (1-2 pages), and contact information for three references. Review of applications ends when the positions are filled.


For instructions on the Interfolio application process, please visit http://tiny.cc/InterfolioHelp.