331 parallel-computing-numerical-methods-"Simons-Foundation" positions at NIST in United States
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analytical methods that are rapid, reliable, and sensitive. We are developing model cell expression systems based on rodent (Chinese Hamster Ovary Cells) that produce monoclonal antibodies at high levels
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consideration will be made to candidates with experience in automation or machine learning. The postdoc will join a group which is focused on pioneering applications of modern machine learning methods, FAIR data
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on improving standoff methods for measuring the flux of carbon dioxide from smokestacks and distributed area sources (5 km x 5 km) by advancing the applications of integrated path differential absorption LIDAR
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interactions, H-bonding force constants, and anharmonic character of the force fields. Continuous-wave and phase-coherent chirped-pulse methods are used to measure the spectra of bulk (pellet) samples, thin
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301.975.6050 Jan Obrzut jan.obrzut@nist.gov 301.975.6845 Description As part of a collaborative NIST-wide program involving structural characterization, modeling, and high-throughput microwave measurement, we
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collisional parameters, such as energy levels, radiative and autoionization rates, collisional cross sections, using the most advanced relativistic methods and codes. With the help of large-scale collisional
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to reliable manufacturing of the next generation computing devices. Computational imaging methods such as coherent diffractive imaging, Fourier ptychography, structured illumination techniques, and other super
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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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RAP opportunity at National Institute of Standards and Technology NIST Applied Optimization and Simulation Location Information Technology Laboratory, Applied and Computational Mathematics
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) and cannabidiol (CBD), as well as numerous terpenes, flavonoids, and fatty acids. It is known that THC, CBD and synthetic cannabinoids with analogous structures can bind to cannabinoid receptors