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Your Environment. Your Health.

Biostatistician – Biostatistics and Computational Biology Branch

Department of Health and Human Services
National Institutes of Health (NIH)
National Institute of Environmental Health Sciences (NIEHS)
Research Triangle Park, North Carolina

The National Institute of Environmental Health Sciences (NIEHS), part of the National Institutes of Health (NIH), is seeking a biostatistician/statistician to collaborate in the statistical design, analysis and interpretation of environmental health studies. 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. Increasingly, research at NIEHS generates high-dimensional data from sources such as epidemiological, genomic, genetic, high-throughput chemical screening experiments, and microbiome studies. Additionally, there are many emerging topics in toxicology related to new “health effects initiatives” within the National Toxicology Program, including experimental studies with new non-cancer health endpoints (e.g. cardiovascular endpoints and developmental neurotoxicity) and challenging areas such as studying chemical mixtures. Such data necessitates the development and application of robust statistical approaches to ensure valid inference. This position will involve both the development and application of new statistical and machine learning methods for the analysis of environmental health related data.

The successful candidate will collaborate extensively with researchers in the BCBB to advance statistical science on the environment and human health. The successful candidate will work with investigators within BCBB, and with investigators across the Institute on motivating data applications at their discretion. Experience in one of the following areas is a plus: Bayesian methodology, machine-learning, environmental statistics, spatial statistics, and others. These are listed as potential areas of expertise, understanding that no single candidate can be an expert in all these areas.

Qualifications: The successful candidate will have strong statistical and computational skills. They need to be skilled in oral and written communication, and have proven experience working productively with multidisciplinary teams. Experience with the analysis of high-dimensional data is desirable. Applicants should have a Ph.D. in statistics, biostatistics, or a closely related field with demonstrated biostatistical 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:

Alison A. Motsinger-Reif, Ph.D.
Chief, Biostatistics & Computational Biology Branch and Principal Investigator
Tel 984-287-3705
alison.motsinger-reif@nih.gov

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 with NR-109 in the subject line to int-appls@niehs.nih.gov that includes both 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 int-appls@niehs.nih.gov. As there are other recruitments ongoing, please instruct your referees to include your name and NR-109 in the subject line of their email. Incomplete and paper applications will not be accepted. Review of applications will begin on August 12, 2019, but applications will be accepted until vacancies have 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.

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