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such as L-PBF over 10 years, and potential applicants can utilize and build upon NIST's repertoire of instruments, facilities, ongoing research, and interdisciplinary network of scientists and engineers
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properties to them, generates a finite element mesh, and performs virtual measurements. The goal is to build a computational platform that can predict the macroscopic behavior of a material from knowledge of
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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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upon NIST's repertoire of instruments, facilities, ongoing research, and interdisciplinary network of scientists and engineers involved in this subject. Applicants may tailor their proposals to make use
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measurements at 18-digit accuracy using an optical clock network. Nature 591, 564–569 (2021). https://doi.org/10.1038/s41586-021-03253-4 [2] Chave, A. D. (2019). A multitaper spectral estimator for time-series
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components. To develop this program in oxide electronics, a successful applicant will have a solid background in programming (Matlab, Python, or equivalent). Experience with any of the following lock
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RAP opportunity at National Institute of Standards and Technology NIST Leveraging Artificial Neural Networks for Enhancing GC and LC-MS Metabolomics Data Interpretation and Integration Location
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analysis capable of communication to other software implementing additional thermodynamic models, contacts with its collaboration network, and computational resources. A successful candidate should be
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are developing machine learning-driven autonomous metrology research systems, with the goal of accelerating the development of self-correcting photonic and quantum sensor networks. These systems combine machine
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. Appl. 21, 054028 (2024). M. W. Daniels et al., Neural Networks Three Ways: Unlocking Novel Computing Schemes Using Magnetic Tunnel Junction Stochasticity, in Spintronics XVI, Vol. 12656 (SPIE, 2023), pp