National Institute of Environmental Health Sciences
Research Triangle Park, North Carolina
The National Institute of Environmental Health Sciences (NIEHS), part of the National Institutes of Health (NIH), is seeking an experienced bioinformaticist/computational biologist to collaborate in the statistical design, analysis and interpretation of genetic and environmental health studies. The appointment will be at the rank of Staff Scientist in the Biostatistics and Computational Biology Branch (BCBB) of the Division of Intramural Research (DIR). The scientific environment at NIEHS provides exciting opportunities for collaborating statisticians and computational scientists. Increasingly, research at NIEHS generates high-dimensional data from sources such as epidemiological, genomic, genetic, high-throughput screening and microbiome studies. This position will involve both the development and extensive applications of new computational methods in bioinformatics and statistical genetics.
The successful candidate will provide support for the development of computational methods to detect genetic risk factors of common, complex traits in human populations and established model organisms, including clinical trials, cell line models, and genetic epidemiology studies. The position will work directly with Dr. Motsinger-Reif in the BCBB, and will work on new and established projects in human genetics, including applications in drug response phenotypes, complex trait mapping, and bioinformatics methods development. Strong computational skills are required, with computer science training and experience preferred.
Salary/Benefits: The successful candidate for this position will be appointed at a salary commensurate with experience and accomplishments with full Federal benefits, including leave, health and life insurance, retirement, and savings plan (401K equivalent).
How to Apply: Interested persons should email a combined single PDF application with BCBB-SSG in the subject line to email@example.com that includes a cover letter, their curriculum vitae and a two-page statement describing their research and collaboration experience. Applicants must also arrange to have three letters of reference in PDF format sent directly to firstname.lastname@example.org. As there are other recruitments ongoing, please instruct your referees to include your name and BCBB-SSG in the subject line of their email. Incomplete and paper applications will not be accepted. Review of applications will begin on April 4, 2019, but applications will be accepted until the vacancy has been filled.
The NIH is dedicated to building a diverse community in its training and employment programs. DHHS and NIH are Equal Opportunity Employers.
Applications from women, minorities, and persons with disabilities are strongly encouraged.
Qualifications: The successful candidate will have strong skills in computation and in oral and written communication and must/should demonstrate proven experience working productively with multidisciplinary teams of biologists, toxicologists, epidemiologists, and/or clinical scientists. Experience with the analysis of high-dimensional data is required. Applicants should either have a Ph.D. in statistics, biostatistics, or genetics, or have a doctoral degree in a related field with demonstrated applied biostatistical and computational experience. Appointees may be U.S. citizens, resident aliens, or non-resident aliens with, or eligible to obtain, a valid employment- authorization visa. For additional information, contact Dr. Alison Motsinger-Reif, Chief, Biostatistics and Computational Biology Branch, at 984-287-3705 (email@example.com).
Internal Number: NR110
The mission of the NIEHS is to discover how the environment affects people in order to promote healthier lives. The studies conducted at NIEHS are often long term and high risk in nature and involve unique components, such as epidemiological studies of environmentally associated diseases, toxicological testing of environmental substances and intervention and prevention studies to reduce the effects of exposures to hazardous environments.