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RAP opportunity at National Institute of Standards and Technology     NIST

Artificial Intelligence for Genomics Reference Materials


Material Measurement Laboratory, Biosystems and Biomaterials Division

opportunity location
50.64.41.C0313 Gaithersburg, MD

NIST only participates in the February and August reviews.


name email phone
Justin Matthew Zook 301.975.4133


NIST has a long tradition of producing highly impactful Standard Reference Materials (SRMs), which typically have a single certified value or exceptionally well characterized property with known uncertainties. New biological “’omics” measurements, particularly sequencing-based methods, can produce 103 to 109 values from biological systems and are transforming biosciences and biotechnology. Yet, the translation of technologies requires greater measurement confidence underpinned by SRMs. Data produced by the NIST-led Genome in a Bottle Consortium led to the development of the first NIST RMs in this class, with widely-used benchmark germline variant calls for seven human cell lines [1].  Artificial intelligence and machine learning hold promise to automate and improve integration of diverse ‘omics technologies, which have different strengths and weaknesses, and establish new RMs. This project would involve developing these methods, including research in deep learning for genomics and “explainable AI”, and collaborating with Genome in a Bottle Consortium members and others from companies, academia, and government.

[1] JM Zook, et al. An open resource for accurately benchmarking small variant and reference calls. Nature Biotechnology 2019, 37, 561.

key words
Artificial intelligence; Machine learning; Data science; Genomics; Sequencing; Precision medicine


Citizenship:  Open to U.S. citizens
Level:  Open to Postdoctoral applicants


Base Stipend Travel Allotment Supplementation
$82,764.00 $3,000.00
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