Postdoctoral Researcher position in Statistical/Generative AI applications in genetics

The Kushal Dey lab (https://www.mskcc.org/research/ski/labs/kushal-dey) in the Computational and Systems Biology program at the Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center (MSKCC), has 1 computational postdoctoral fellow position available. 

The postdoc will be working with Dr. Dey and other collaborators from MSKCC, Columbia University, Stanford University, and Harvard T.H.Chan School of Public Health on

A.   Analyze multi-ancestry genetic data from biobanks and integrate with functional genomic, multimodal transcriptomics and perturbation experiments.
B.   Perform GWAS variant-to-function by leveraging multi-omics data, spatial omics data and CRISPR Perturb-seq assays. C.   Build new machine learning and statistical approaches to analyze large-scale GWAS data and build integrative models of gene regulation in human cells.

We welcome applications from candidates with an exceedingly strong quantitative background in genetics, biostatistics, computational biology, or other related domains. The applicant would be required to have prior experience working with genetic data, resulting in first/co-first author publication/preprint. The candidate must be proficient in computing, with expertise in R and/or Python.

The candidate’s primary affiliation will be through the Sloan Kettering Institute, MSKCC located on the Upper East Side of New York City. It is part of the vibrant Tri-Institutional Research campus adjacent to Rockefeller University and Weill Cornell Medical College. Sloan Kettering offers competitive postdoc salaries and convenient subsidized housing.

The candidate will have weekly meetings with Dr. Dey and will be working closely with collaborators from various consortia like ADSP, ENCODE, and IGVF.

To apply, please send a CV, a brief cover letter outlining your interest, and names/contact information for three references to both the following email address. 

[email protected]