| The Department of Statistics at the University of Michigan invites applications for a full-time postdoctoral associate to develop new statistical methods for genomics with Assistant Professor Jeffrey Regier. The ideal candidate will have a background in Bayesian statistics and machine learning, strong programming skills, and a working knowledge of cell biology. Previous experience with scRNA-seq data, PyTorch, and variational inference is desirable but nonessential.
The focus of this position is developing rigorous statistical methods for interpreting single-cell transcriptomics data. Possible research topics include 1) developing statistical methods to infer gene regulatory networks based on CRISPR knockout experiments, and 2) developing statistically identifiable models to remove scRNA-seq batch effects. Data will be provided by Immunai. You would have the opportunity to interact with Immunai’s scientists to influence their experimental design, and, if desired, to work as a visiting researcher in Immunai’s NYC office during the summer.
A Ph.D. in statistics, biostatistics, bioinformatics, computer science, or a related discipline is required. The position starts Fall 2021 and lasts for two years, with a possibility of renewal. It is a 100% research appointment. A computer and an annual travel stipend will be provided, in addition to the excellent benefits that U Michigan provides to all postdoctoral associates.
To apply, please submit a CV, a cover letter, a research statement, and contact information for three references. Applications will be reviewed on a rolling basis; all applications received while this job ad remains posted on mathjobs.org will be given full consideration.
The University of Michigan is an equal opportunity/affirmative action employer. We welcome applications from members of all groups traditionally underrepresented in STEM. |
finished (2021/03/22, finished 2021/09/02, listed until 2021/05/01)