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NIST only participates in the February and August reviews. In many application areas, materials development increasingly involves manipulating the local atomic order to optimize properties
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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with 1000× increase in time resolution and 10× improvement in spatial resolution over prototypes. Such an instrument enables to measure the structure of heterogeneous systems including ageing concrete
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Your Job: Digital methods for inverse materials design are essential to efficiently create new, sustainable and recycling-adapted structural metals. Alloys with a reduced number of elements, so
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cooperating with each other, but in many cases competing for individual gains. This structure may not always work for the benefit of science. The purpose of this project is to use game theory and computational
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group includes Project Delivery, Maintenance & Construction, Campus Utilities & Operations, Building Services, Transportation Services and Safety. Supporting these groups, as well as the separate
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especially for the growth of optimized devices. For these atomic structural characterizations, the laboratory has a latest-generation MET JEOL ARM200F Cold FEG corrected (Cs), equipped with ADF/ABF detectors
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interdisciplinary methods (such as artificial intelligence, digital twins, AR/VR, operations research, human factors, structural health monitoring, robotics) in the research focus of Industrialized Construction
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today. Their convergence has the potential to redefine how we simulate, optimize, and understand complex physical systems. Integrating AI into quantum computers and simulators can help overcome current
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, turbines rotate at speeds up to 100,000 rpm to deliver propellant to the rocket engine at high flow rates and optimized pressures. At such extreme conditions, mechanical supports like ball bearings alone