Pay Rate: $50/hr w2

Extensive experience in large-scale genetic/genomic data analysis including one or more of the following areas of expertise:
Understanding of principles of genetic epidemiology
Association analysis with array- and sequence-based genetic data
Analysis of sequence-based molecular assay data (eg RNA-Seq) including differential expression methods, single-cell sequencing data (eg scRNA-Seq, scATAC-Seq) and/or proteomic data
Integration of genetic and molecular data for multimodal analyses
PhD (or Masters with significant experience) in Statistical Genetics, Computational Biology, Bioinformatics, Genetic Epidemiology, or a related field
Fluent in R, python, and shell scripting. Some familiarity with C++ will be a plus
Experience working with git and high performance computing (e.g. the slurm scheduling manager)
Curiosity and desire to learn more about human genetics, bioinformatics, and biology
Ability to produce high-quality analysis results with minimal supervision. This includes meeting key deadlines and making sensible independent decisions
Good communication skills and experience working as part of a team.