141 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"SciLifeLab" positions at NIST in United States
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alloys, carbon-based composites, and solid-state-biomolecule hybrid structures. Our data-driven development uses cheminformatics methodologies combined with machine learning methods to produce predictive
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our data infrastructure is set up so that all microscopy datasets from all users are collected and archived at a central file location. In 2020, we have begun curating and labeling microscopy datasets
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Development of Hyperspectral Raman Imaging for Biology and Medicine: Optical Platform and Data Mining Methods NIST only participates in the February and August reviews. Molecules vibrate with
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.; McLinden, M. O., Nuclear Magnetic Resonance (NMR) Spectroscopy for the in situ Measurement of Vapor-Liquid Equilibria. J. Chem. Engr. Data 2020, https://pubs.acs.org/doi/10.1021/acs.jced.0c00113 . Nuclear
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of integration, encompassing AM equipment, data, and simulation tools. To facilitate this, this opportunity focuses on building the necessary data and computation infrastructure to enable the Integration
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the development of analytical methodologies, from both instrumentation and informatics standpoints, for the multifaceted and convoluted data that are obtained from complex biological, chemical, and forensic samples
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@nist.gov 301 975 2093 Description This opportunity focuses on the development of analytical methods and/or data processing techniques that could be used to advance drug detection and identification (or drug
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301.975.4579 Description As the demand for high resolution, high content imaging increases, the cost and challenges of acquiring, storing, processing, and analyzing today’s very large imaging data sets are even
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involving an actual or planned nuclear attack. Conclusions drawn from this collected data coupled with law enforcement and intelligence information may support attribution—the identification of those
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) motivates research in Knowledge Representation and Reasoning (KRR). The successful applicant would have an opportunity to apply their expertise in semantic web, linked data, and knowledge graphs to the field