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driven flows; Combustion; Computational fluid dynamics; Fire modeling; Heat transfer; Large eddy simulation; Numerical combustion; Thermal radiation; Turbulent flows; Eligibility citizenship Open to U.S
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RAP opportunity at National Institute of Standards and Technology NIST Immersive Visualization Location Information Technology Laboratory, Applied and Computational Mathematics Division
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structural techniques for probing the interface, such as SEIRAS and STM, with computational methods to develop new electrochemical models. The computational work focuses on combining DFT methods
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quantitative analysis including rheology, DSC, scattering, etc. Concurrently, computational modeling will be used to predict both structure-property relationships and degradation rates based on the number and
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will be complemented by computer model simulations using available capabilities based on methods such as density functional theory (DFT). [3] [1] J. Ilavsky, F. Zhang, R.N. Andrews, I. Kuzmenko, P.R
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NIST only participates in the February and August reviews. Co-advisor: Dr. Angela Stelson, S-parameters calibration lead. Commercial acoustic spectroscopy is stuck below 300 MHz, which limits our understanding of materials. For communications technology, the lack of acoustic data limits the...
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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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the potential of quantum states of light for advanced measurements and computation, integration in a chip-scale nanophotonic environment is required. In particular, the integration of single-photon sources with
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RAP opportunity at National Institute of Standards and Technology NIST Enabling Advanced Functionalities in Photonics using Low-Dimensional Semiconductors Location Material Measurement Laboratory, Materials Measurement Science Division opportunity location 50.64.31.B8238 Gaithersburg,...
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classification of scientific publications by their relevancy have been done at TRC. A successful applicant is expected to have a strong background in computer sciences, particularly in AI, NLP, and ML. No specific