OMRF is an independent, not-for-profit biomedical research institute adjacent to the University of Oklahoma Health Sciences Center (OUHSC) campus in Oklahoma City. Oklahoma City offers a dynamic and flourishing downtown area, with low cost of living, short commute times and a diversified economy.
OMRF’s excellence can only be fully realized by individuals who share our commitment to diversity, equity and inclusion. Successful candidates will demonstrate commitment to these values. OMRF is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to gender, sexual orientation, gender identity, race, color, national origin, age, religion, disability, veteran status or any other legally protected characteristic.
We offer competitive salaries and comprehensive benefits including, medical, dental, and vision insurance, minimum 8% company retirement contribution, vacation and sick leave, paid holidays, onsite café, free onsite fitness center with access to personal trainer, free parking and much more! Relocation assistance available for those located 50 miles outside of Oklahoma City metro and out of state. Learn more about our benefits here.
The Nath Lab is seeking a highly motivated, hardworking and organized team player (Post-doctoral Fellow / Assistant Staff Scientist) to join our effort to understand genetic mechanisms of lupus, an autoimmune disease. Using whole genome search, our lab has identified several genes/genetic variants, associated with lupus susceptibility. Now we are trying to understand the specific functional effects of those lupus associated genetic variants, using cell lines, patients-derived primary immune cells or tissues. We will apply various modern techniques for studying features of three-dimensional (3D) genomic organization such as 3C, Hi-C, ChIP-Seq, and genome editing using CRISPR/Cas9. Candidate will be involved in the analysis of human genetic data and the development of computational methods, which requires a mix of computational skills, statistical knowledge, creativity and biological insight. Specifically, candidate will identify novel therapeutic targets and biomarkers from the investigation of human genetic variation (GWAS, Next Gen Sequencing) with disease status and intermediate variables using cutting-edge techniques in Statistical Genetics. Candidate will develop and apply methods for the integration of GWAS summary results with other types of data e.g. eQTL, mQTL, functional genomic annotations, gene networks, estimation/partitioning of heritability, Mendelian Randomization to understand causal direction, and fine mapping. Candidate will collaborate with experimental and clinical scientists to address target mechanism specific questions and seek to support investment decision making with genomic insights.
Ph.D. in a biological science or other relevant area, M.D., or equivalent.
Knowledge of statistical genetic methods for gene-mapping for complex traits, and computer programming skills (e.g. familiarity with UNIX-like OS, and at least one programming language) are required.
Prefer candidates to have a doctoral degree in epidemiology, biostatistics, genetics, bioinformatics, statistics, computer science or related fields.
The successful applicant is expected to have a strong interest in genetic epidemiology of complex traits and will have experience in both the application/implementation of established methods for genetic linkage and association studies, and in methods development. Experience in genomics, cloning and functional characterization of genes will get preference.