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Statistical Methods and Applications in Metagenomics and the Microbiome

National Institute of Environmental Health Sciences, Research Triangle Park, NC

Position Description:

A postdoctoral position is available in the Biostatistics and Computational Biology Branch (BCBB) at the National Institute of Environmental Health Sciences, NIH, in Research Triangle Park, North Carolina co-mentored by Drs. Alison Motsinger-Reif, Shanshan Zhao and Stephanie London.  These investigators represent an exciting interdisciplinary team with expertise in bioinformatics, statistics, and genetic and environmental epidemiology.

https://www.niehs.nih.gov/research/atniehs/labs/bb/staff/motsinger-reif/index.cfm

https://www.niehs.nih.gov/research/atniehs/labs/bb/staff/zhao/index.cfm

https://www.niehs.nih.gov/research/atniehs/labs/epi/pi/genetics/index.cfm

The microbiome plays a vital role in maintaining health, and imbalances in the microbiome are associated with a wide variety of diseases. Understanding whether and how the microbiome is associated with particular health conditions is a focus of many modern microbiome studies, whether in humans or in model organisms, with the hope that a deeper understanding of these associations may lead to more effective prevention and treatment regimens. However, how best to analyze data from microbiome profiling studies remains unclear. The high dimensionality, compositional nature, intrinsic biological structure, and limited availability of samples pose substantial statistical challenges. 

The successful candidate will develop and apply methods for the broad category of metagenomics/microbiome data.  There are a number of possible methodological challenges to be addressed.  Example projects include addressing issues related to limit of detection challenges with censoring approaches, developing concepts of canonical distance correlations on a simplex to describe dependence and networks among microbes within and between samples, and others. These methods will be applied to data on microbiota from house dust in a study of a US farming population generated with two different sequencing methods : 16s rRNA and metagenomics.

Qualifications:

Candidates should have or be very close to obtaining a Ph.D. in biostatistics, statistics, bioinformatics, genetics, computational biology, data science or closely related areas. Programming skill is required. Excellent communication skills and fluency in both spoken and written English are essential.

To Apply:

Interested candidates should submit their curriculum vitae, a detailed statement of their research interests, and the names and contact information for three references to Dr. Alison Motsinger-Reif at motsingerreifaa@niehs.nih.gov.

 

This post will be available until July 6, 2020.

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