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Position is 100% grant funded and one year to start with extensions contingent on funding, performance, and needs of the lab.
The David Lab at Duke University (www.ladlab.org) is recruiting a Biostatistician I to join a team of scientists developing and using new DNA sequencing tools to study diet and the gut microbiome. We are particularly interested in creating new ways to measure and analyze food intake, which is essential for monitoring and improving human health. We are developing DNA sequencing-based techniques that allow us to track the dietary plant and animal species that people consume. Our techniques allow us to generate objective data on intakes of over 450 plant and animal species that individuals eat and is robust to differences in memory/recall; the output data are also standardized across languages and cultures using the universal language of DNA. We are applying these tools to biospecimens from populations across North Carolina and the world. Data resulting from these studies will allow us to compare our biomarker of diet to traditional surveys of dietary intake, as well as perform systems biological studies of human food intake. The results of our studies will also allow us to create new models of disease risk and examine geographic, cultural, behavioral, and socioeconomic determinants of diet. These projects are funded by awards from the Chan Zuckerberg Initiative, the National Institutes of Health, the Gerber Foundation, and the Burroughs Wellcome Fund.
Potential projects are expected to involve:
- Developing, maintaining, and running bioinformatic pipelines for processing genomic data
- Maintain and curate databases of reference genomic data
- Design and run statistical tests on datasets of food intake
- Create and maintain websites/apps for visualizing food intake data
- Writing scientific manuscripts for peer-review reporting findings from the work
Work requires a Bachelor's degree in (bio)statistics or related field. We are interested in applicants who have at least a Bachelor's Degree that would be relevant to mathematical, computational, or statistical analyses of 'omics, epidemiological, or other projects related to data science and machine learning. No experience is required beyond that obtained through education, but familiarity with R, the command line, and version control will be helpful, as would experience with alternate languages and tools. Expertise in nutrition, anthropology, agriculture, phylogenetics, or environmental science may additionally be relevant. We are broadly interested in inter-disciplinary thinkers and expertise across all of these areas is not expected or required.
Work requires a Bachelor's degree in (bio)statistics or related field.
No experience required beyond that obtained through education.
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