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.
The Nath laboratory is seeking a highly motivated, self-starter senior level scientist with 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.
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.
Bachelor’s degree in Bioinformatics, Biostatistics, Computer Science, Genetics, Epidemiology, computational sciences or relevant field or a combination of relevant experience and education.
Must have knowledge and experience 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.
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