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NIST only participates in the February and August reviews. As of today, there is a plethora of cyber-physical instruments consisting of physical sensing (e.g., microscopy imaging) and cyber (digital) Artificial Intelligence (AI)-based predictions. These instruments raise concerns about safety...
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RAP opportunity at National Institute of Standards and Technology NIST Applied Mathematics of Soft, Fluid, and Active Matter Location Information Technology Laboratory, Applied and Computational
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of structural responses. References Wong KKF, Speicher MS: “Improved Method for the Calculation of Plastic Rotation of Moment-Resisting Framed Structures for Nonlinear Static and Dynamic Analysis”. Computational
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of the constraints on sequencing (read length, depth), and informatics (e.g., database composition, algorithm biases). Proposals should address these challenges with strategies to evaluate the metagenomic
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center. Applicants are expected to be skilled in one of the programming language such as C++/C, Perl, Matlab, or R, and have majored in Chemistry, Statistics, or Computer Science. Reference Yang X, et al
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parallel algorithms, execution of algorithms in the computer cloud, to delivering on-demand measurements over the Web. key words Image processing; Machine learning, Computer vision; Statistical methods
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RAP opportunity at National Institute of Standards and Technology NIST Metabolomic and Lipidomic Research: Emphasizing Advanced Data Analysis, Metabolite/Lipid Annotation, and Functional Pathway Elucidation Location Material Measurement Laboratory, Chemical Sciences Division opportunity...
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jessica.reiner@nist.gov 843.460.9894 Description The Analytical Chemistry Division has an ongoing program to improve the quality of analytical chemical measurements made in marine environmental research through
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understanding of the physics of the QAHE necessary to design and develop new quantum resistance standards. Additional applications in quantum information science (QIS) can be envisioned for robust QAHE devices
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these models do not account for realistic conditions and require lengthy computational time. In order to overcome the practical challenges and numerical bottlenecks, the Fire Research Division of NIST’s