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STFP Home sign in | focus RAP opportunity at National Institute of Standards and Technology NIST Materials Discovery Using Synchrotron Radiation, Machine Learning, and Artifical Intelligence
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(JARVIS) for data-driven materials design" https://www.nature.com/articles/s41524-020-00440-1 2. https://jarvis.nist.gov/ 3. https://www.nist.gov/people/kamal-choudhary Keywords Machine learning
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Carlo, GW, and other advanced techniques are oftentimes needed to correctly describe correlated electronic systems. In recent years, electronic structure methods have been coupled to machine learning
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: https://www.nist.gov/people/peter-bajcsy Keywords imaging; image analyses; machine learning; software engineering Eligibility citizenship Open to U.S. citizens level Open to Postdoctoral applicants
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an autonomous platform for developing and testing novel MOF materials for applications in carbon capture (https://doi.org/10.1016/j.xcrp.2022.101063). Successful candidates must have a background in
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create an environment rich with sensor data and distributed control intelligence that can be applied to solve these problems through the application of machine learning, intelligent optimization
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; Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL). 1 - Cumeras, R., T. Shen, L. Valdiviez, Z. Tippins, B. D. Haffner and O. Fiehn (2023). "Differences in the Stool Metabolome between
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github.com/usnistgov/ThreeBodyTB.jl), cluster expansion, classical potential development, and machine learning. In addition to work on specific problems, I work on developing new first principles-based
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economically viable, which requires reduced acquisition time, advanced scanning strategies, and novel reconstruction and defect-detection algorithms based on artificial intelligence and machine learning (AI/ML
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vulnerability specifications, as well as for formal proofs of code correctness and existence of bugs/faults. BF makes vulnerabilities machine-understandable and supports the development of BF-based systems