Postdoctoral fellow in statistical and computational genomics

Memorial Sloan-Kettering Cancer Center
United States New York new york

Description

We are seeking a highly motivated candidate, interested in statistical and computational methods development and application in immuno-oncology studies, for a position as a postdoctoral fellow. This position will focus on analyzing high-dimensional flow cytometry data and single-cell RNA sequencing in a large dataset of patients treated with immune checkpoint blockade (ICB) with rich clinical annotation. The candidate will have the opportunity to lead the development of novel statistical and computational approaches and work with world’s leading immuno-oncology experts.


Qualifications

Applicants should hold a Ph.D. degree in statistics, computational biology, bioinformatics, or a related field, ideally with experience in high dimensional data analysis. The successful candidate should have solid methodological training in statistics, be comfortable working with large data sets, proficient in at least one of the statistical programming languages R/Matlab/Python and have experience working on Unix/Linux systems and basic shell scripting. Prior experience with either flow cytometry, CYTOF or single-cell RNA sequencing data would be an asset.


Start date

As soon as possible

How to Apply

To apply, send a cover letter, cv, and the names of 3 references to Ronglai Shen (shenr@mskcc.org): Memorial Sloan Kettering Cancer Center, 485 Lexington Avenue, New York, NY 10017.