Staff Scientist

University of Chicago•Chicago, IL

15d•$80,000 - $100,000

About The Position

The Staff Scientist will provide scientific leadership and hands-on research expertise to the Precision Health Informatics Lab (PHIL), supporting the design, execution, and interpretation of large-scale genomic and phenomic studies. The position advances biobank-scale research into rare genetic variants and their clinical effects, connecting computational methods development with biological and clinical interpretation. PHIL develops and applies computational and informatics methods to translate genomic and clinical data into insights about human health and disease. Its work spans genomics, electronic health record (EHR) data, population-scale biobank research, phenomics, machine learning, large language models, and generative AI. The lab develops computable phenotype algorithms and integrates EHR, survey, genomic, and other health data to investigate gene-disease relationships, genetic variation, and precision medicine applications. The Staff Scientist will guide gene-disease discovery and phenotype development, interpret analytical findings using biomedical knowledge resources, contribute to studies of rare genetic diseases, and collaborate with and mentor programmers, analysts, and trainees. The role also contributes to scientific writing, grants, reports, and presentations.

Requirements

PhD in a related field.
5–7 years of work experience in a related job discipline.
Demonstrated research experience in human genetics, genomic epidemiology, or clinical informatics.
Strong understanding of statistical genetics methods, such as GWAS, PheWAS, or related approaches.
Experience working with EHR-linked biobank data.
Track record of scientific publication and ability to communicate complex findings clearly.
Excellent written and verbal communication skills.
Ability to work independently and collaboratively in a multidisciplinary environment.
Strong manuscript and proposal writing skills.
Ability to work with people from different backgrounds.
Strong problem-solving skills.

Nice To Haves

PhD in genetics, genomics, bioinformatics, epidemiology, or a related field.

Responsibilities

Design and lead analytic strategies for gene-disease discovery studies, including GWAS, PheWAS, and integrative multi-omic approaches.
Guide the development of computable phenotype definitions for diseases, drug effects, and other conditions, ensuring clinical and biological validity of EHR- and survey-derived phenotypes.
Interpret genomic and phenomic analysis findings using biomedical knowledge resources such as OMIM, Human Phenotype Ontology, and DrugBank to prioritize gene-disease and gene-function hypotheses.
Contribute to the scientific direction of studies identifying and characterizing novel genetic diseases and gene effects through clinical investigation of individuals with rare variants.
Mentor and collaborate with programmers, analysts, and trainees on study design, statistical approaches, and biological interpretation.
Prepare manuscripts, reports, grants, and presentations to communicate research findings to scientific and clinical audiences.
Stay current with emerging methods in statistical genetics, phenomics, and precision medicine to inform research directions.
Collect data and perform analyses, and facilitate and promote research projects by providing scientific or intellectual information.
Create first drafts of scientific writing and publications, including protocols and grants.
Perform other related work as needed.