Computational Biologist – Section of Genetic Medicine (GWAS, metabolomics and polygenic risk)

The University of Chicago's Section of Genetic Medicine, which focuses on quantitative genetics, systems biology, genomics and computational biology, seeks a Computational Biologist to develop and apply statistical and computational tools across NIH-funded projects. The work integrates large-scale GWAS with metabolomics data to uncover mechanisms of complex diseases and develops polygenic risk scores that transfer genetic signals across human populations and model organisms to study addiction-related traits, COPD, type 2 diabetes and other common diseases.

Responsibilities include analysing RNA-seq, whole-genome and single-cell data, training deep learning models to improve on traditional statistical genomics methods, collaborating with disease and genomics experts, publishing, and mentoring students. The pay range is $60,000–$80,000.

College or university degree in a related field and 2–5 years of related work experience. Preferred: master's or doctoral degree in computational biology, bioinformatics, statistics, physics or another quantitative discipline; deep learning in genomics and large language models; large datasets, distributed computing and databases; reproducible workflows (GitHub, Snakemake, Nextflow); R and/or Python. Resume and cover letter required.