189 computer-science-quantum-"https:"-"https:"-"https:"-"https:"-"U.S"-"U.S" positions at NIST
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technologies to manipulate biological macromolecules such as DNA, and the controlled degradation of tissue engineering scaffold or drug delivery materials. To optimize performance and to design new applications
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NIST only participates in the February and August reviews. This program involves multimodal imaging techniques that use magnetic resonance imaging (MRI) as either a base or as a complimentary
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NIST only participates in the February and August reviews. This research opportunity is focused on developing advanced chemical characterization and analytical chemistry tools, data and research
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interaction networks within naturally occurring microbiomes (i.e., 10^2-10^3 constituent species). This project lies solidly at the interface of microbiology and microbiome engineering, analytical and
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prediction. In collaboration with NASA, NOAA, and the USGS, NIST develops technology to advance the calibration and characterization of ground- and space-based infrared, optical, and temperature sensors
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employed. This involves the computational determination of 3-D features of a specimen from a series of their 2-D projections. By carefully preparing the specimen, designing the experimental acquisition, and
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crystallography and spectroscopy are fundamental and imperative in the investigation and development of condensed matter sciences. We will widely use these methods to study the crystal structures of novel materials
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characterization to nanophotonic integration. Our project is collaborative and interdisciplinary, and we seek outstanding applicants with high motivation and strong backgrounds in the physical sciences. Contact
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orientations in most engineering materials have some preferential distribution due to processing conditions and deformation history, referred to as crystallographic texture. This texture affects the initial
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technology development community and cell line repositories to design reference transcriptome samples, and then develop methods to integrate transcriptome sequencing data from short and long read technologies