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) machine learning. The project will focus on one or a combination of the following focus areas, tailored to the candidate’s expertise and interests: Developing numerical models for the coupled mechanical
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) and molten salts - Optimization of synthesis conditions followed by physicochemical characterization of the materials obtained - Synthesis of MXene and hard carbon composites - Preparation of electrodes
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the Forschungsverbund Berlin (https://www.fv-berlin.de/ ) and the Leibniz Association www.leibniz-gemeinschaft.de . You can find more details on the institute webpage: www.ikz-berlin.de . The Section Fundamental
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. This position will also design, build, test, and demonstrate new capabilities for numerical simulation of the oceanographic environment for assessment of AUV system flight performance. This position will develop
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in drop towers, parabolic flights, and sounding rockets. Optimizing material formulations based on feedback from experimental and numerical simulations to enhance fire safety in space environments
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to industry, Vanguard has also the mission of developing an ecosystem of related start-ups. For more information about our Center, please visit our webpage: https://vanguard.um6p.ma/ Offer description
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 18 hours ago
professional training opportunities for career growth, skill development and lifelong learning and enjoy exclusive perks for numerous retail, restaurant and performing arts discounts, savings on local child
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Manufacturing technique. By combining modelling, in-situ monitoring, process optimization, and advanced materials characterization, the project aims to produce crack-free tungsten components. The Department
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North Carolina A&T State University | Greensboro, North Carolina | United States | about 1 month ago
applications. Specific research and teaching areas include, but are not limited to: Custom hardware architectures, including AI/ML accelerators, and domain-specific computing methods Design and/or optimization
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. Background in numerical analysis and/or optimization, with interest in error estimation, convergence, and robustness to noise. Experience with geospatial data (LiDAR/photogrammetry/GIS) and handling large