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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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STFP Home sign in | focus RAP opportunity at National Institute of Standards and Technology NIST Coupling electronic structure methods, artificial intelligence, and data-driven approaches
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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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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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images and multiple channels, (d) optimizing 2D projection viewpoints (dose reduction and time savings), (e) applying artificial intelligence and traditional machine learning models to noise
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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