The Kushal Dey Lab is seeking a highly motivated and successful individual with a background in statistical genetics and genomics. The candidate will work closely with Dr. Dey, other quantitative PhDs in the group and with collaborators at MSK, Weill Cornell Medicine, The Rockefeller University, and other institutions. Questions we aim to answer include – (1) Which statistical and machine-learning approaches and methods provide maximum power to identify genes, gene pathways and genomic regions that are critical for disease, (2) What is the contribution of different omics data (RNA-seq, ATAC-seq, Perturb-seq, spatial transcriptomics) to the heritability of complex disease, and how this informs disease association and polygenic models of disease risk, (3) How common and rare are variants contribute to disease and disease-related function in diverse populations, while accounting for the effects of selection.
The ideal candidate should have:
- Exceedingly strong quantitative research background
- Practical experience working with large rea;-world genetic data sets, developing new methods, and producing high-quality published work
- Proficient in computing, with expertise in R and/or Python
- Preference will be given to candidates with degrees in computer science, statistics, computational biology, and other quantitative fields.
Salary Range: $63,755 - $100,940