Founded in 1946, the Oklahoma Medical Research Foundation (OMRF) is among the nation’s oldest, most respected independent, nonprofit biomedical research institutes. OMRF is dedicated to understanding and developing more effective treatments for human diseases, focusing on critical research areas such as Alzheimer’s disease, cancer, lupus, Multiple Sclerosis, and cardiovascular disease. OMRF follows an innovative cross-disciplinary approach to medical research and ranks among the nation’s leaders in patents per scientist.

Located in Oklahoma City, a city that offers a dynamic and flourishing downtown area, with low cost of living, short commute times and a diversified economy, OMRF has been voted one of the Top Workplaces since the inception of the award. This achievement has been accomplished thanks to OMRF individuals who share a unified understanding that our excellence can only be fully realized with a commitment to diversity, equity, and inclusion. Successful candidates will demonstrate commitment to these values.

Benefits
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.

OMRF is an Equal Opportunity/Affirmative Action/Veterans 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.

The Nath Lab is seeking a highly motivated, self-starter to join the lab as a Senior Data/Bioinformatics Analyst. The successful hire will have the ability to work with optimal resources and little direct supervision to address important questions in the genetics and genomics of systemic lupus erythematosus (SLE or lupus), an autoimmune disease. Using large-scale genome wise association studies (GWAS), 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 from patient-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, RNA-seq and genome editing using CRISPR/Cas9 based techniques. Successful candidate will be proficient in a wide range of analytical methods and the use of bioinformatics/genetics software for analyzing and interpreting various types of data. Preference will be given to candidates with thorough knowledge and experience in GWAS data analysis. The role involves analyzing human genetic and genomic data and developing computational methods, requiring a blend of computational skills, statistical knowledge, creativity, and biological insight. Key tasks include identifying novel therapeutic targets and biomarkers by investigating human genetic variation (GWAS, Next Gen Sequencing) and integrating GWAS summary results with other data types like eQTL, mQTL, and functional genomic annotations. Preference will be given to candidates with thorough knowledge and experience in GWAS data analysis. 

*This is an onsite position located in Oklahoma City, Oklahoma*

Bachelor’s degree in Mathematics, Bioinformatics, Statistics or relevant field such as Biology or Genetics, and 2 years of relevant experience/training or combination of education and experience.

Knowledge in mathematical, programming, databases and computer system fundamentals, and peripheral devices; knowledge of C, C++, PHP, SAS, Ruby, Perl, Python, JAVA, RBP and/or similar programming languages; skill in analyzing problems, identifying alternative solutions, and to communicate effectively both orally and in writing; ability to work with employees at all organizational levels, to solve a variety of problems and recommend and implement viable solutions; in more senior levels.

Master’s degree in Bioinformatics, Biostatistics, Computer Science, Genetics, Epidemiology, computational sciences or relevant field or Ph.D. in Biostatistics/Bioinformatics desired.

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 genetics association studies, and in methods development.