Staff Scientist, Genomics of Autoimmune Rheumatic Disease Section

MGB fosters outstanding basic research and serves as a model for translational research, emphasizing the compassionate and scientifically rigorous application of basic science discoveries at the bedside. For more information visit the Medical Genomics Branch website.

GARDS focuses on the genomics and epidemiology of human autoimmune rheumatic diseases, particularly systemic lupus erythematosus and Sjögren’s disease in multi-ethnic populations. Current research efforts include the integration and analysis of multiple omics technologies/data (including DNA sequencing, DNA methylation, chromatin accessibility, transcriptomics, metabolomics and exposomics) with phenotypic data.

The successful candidate will provide bioinformatic and statistical support as a staff scientist for the research program of Lindsey A. Criswell, M.D., MPH, D.Sc., the Medical Genomics Branch adjunct investigator and director of the National Institute of Arthritis and Musculoskeletal and Skin Diseases. Specifically, this support will include the following activities: accessing, extracting and preparing data for analysis; developing and maintaining bioinformatics pipelines; conducting analysis of genomic and molecular epidemiology data within and across omic platforms including the use of integrative analytic methods; organizing results into clear presentations and concise summaries of work; and maintaining experience with state-of-the-art bioinformatics tools and data repositories. The candidate will also participate in mentoring and training the next generation of scientists.

The successful candidate must hold a doctoral degree in bioinformatics, biostatistics, computer science, computational biology, epidemiology, genomics or other related disciplines. The ability to communicate effectively in speech and in writing is important, as demonstrated by a track record of publications in peer-reviewed literature as part of a research team. The successful applicant will possess many (although not necessarily all) of the following skills: experience with processing and analyzing large datasets for at least two of the following: next-generation sequencing, methylomics, chromatin accessibility, transcriptomics, metabolomics or exposomics; experience with processing and analyzing single cell datasets; experience with software that is publicly available through GitHub and other sources; proficiency in R/Bioconductor; proficiency with public bioinformatics databases (e.g., UCSC Genome Browser, ENCODE, 1000 Genomes, dbGAP, GTEX); proficiency with bash scripting and working in a Linux environment (especially a computer cluster environment); proficiency with core statistical and bioinformatics methods (e.g. linear regression, logistic regression, eQTL analysis, colocalization analysis, etc.); and a demonstrated ability to self-educate in current and evolving bioinformatics techniques and resources.

Applications are currently being accepted on a rolling basis.

Selection for this position will be based solely on merit, with no discrimination for non-merit reasons such as race, color, religion, gender, sexual orientation, national origin, political affiliation, marital status, disability, age or membership or non-membership in an employee organization. NIH encourages the application and nomination of qualified women, minorities and individuals with disabilities. NIH provides reasonable accommodations to applicants with disabilities. If you require reasonable accommodation during any part of the application and hiring process, please notify us. The decision on granting reasonable accommodation will be made on a case-by-case basis. This position is subject to a background investigation. Salary is commensurate with research experience.

Interested individuals should email a cover letter, curriculum vitae, brief summary of research interests and experience and three letters of reference to Lindsey Criswell, lindsey.criswell@nih.gov.

HHS, NIH and NHGRI are Equal Opportunity Employers