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Robotic Systems for Smart Manufacturing Program is developing the measurement science needed to enable manufacturers to characterize and understand the performance of robotics systems within
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employed. This involves the computational determination of 3-D features of a specimen from a series of their 2-D projections. By carefully preparing the specimen, designing the experimental acquisition, and
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simulation techniques. In addition, simulations and examination of the overall separation process may require computational studies across multiple length scales. key words Modeling; Nanotube; Molecular
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NRC Programs at National Institute of Standards and Technology This page provides specific information related to the NRC Research and Fellowship Program at NIST. Use the navigation on the left
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RAP opportunity at National Institute of Standards and Technology NIST MEMS-Based Scanning Probe Microscopy Location Physical Measurement Laboratory, Engineering Physics Division opportunity location 50.68.31.B7380 Gaithersburg, MD NIST only participates in the February and August...
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industries and research sectors. Our research group is interdisciplinary, drawing from diverse previous research experiences including wet-lab and computational work. Interested candidates are invited to reach
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care vision would involve the merging of technological advancements in several threads computing, imaging, and information technology; health care practice; and health care technology. We are interested
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RAP opportunity at National Institute of Standards and Technology NIST Modeling Complex Microstructures Location Information Technology Laboratory, Applied and Computational Mathematics Division
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Measurement Science to Advance Understanding of Chemical Equilibria in Natural Waters NIST only participates in the February and August reviews. NIST has a long-standing program in electroanalytical
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experiments and datasets for model validation of multi-phase computation fluid dynamics (CFD), discrete element method (DEM), or data-driven modelling. Measurement of defect types and populations using micro- x