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NIST only participates in the February and August reviews. There is a growing need for high-performance materials for various technological applications. To address this need, the NIST-JARVIS (https
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Vision and Graphics, Statistical Learning, and Bioinformatics. Please visit the website at https://www.polyu.edu.hk/dsai/ for more information about DSAI. Duties The appointee will be required to: (a
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energy density matter , High Energy Experimental , High Energy Physics , high energy physics or mathematical physics , High Energy Theory , High Energy Theory Group , High Performance Computing
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Ecole Nationale des Ponts et Chaussées (ENPC) | Champs sur Marne, le de France | France | 7 days ago
physics. The PERMACHANGE project builds on high-performance computing (Orgogozo et al., 2023, Xavier et al., 2024) and hybrid modelling (Chinesta et al., 2020; Champaney et al., 2022) for developing a site
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research internships. Criteria of the candidate: PhD in the field of Cryptography, Computer security or any related field. Strong publication record in high impact conferences / journals. Very good
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Palma, to several satellites such as ESA’s Solar Orbiter, NASA’s IRIS and SDO, and in the near future MUSE. The group is a major user of local and national High-Performance Computing facilities. RoCS, and
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as assigned Unit URL https://www.uidaho.edu/tribal-relations Position Qualifications Required Experience Three years performing administrative, office and/or program support functions Required
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Application Deadline: 01 June 2026 Details Project Overview We are seeking a highly motivated PhD candidate to undertake cutting-edge research in the field of Additive Manufacturing (AM) of high-performance
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, Apprenticeship Program, and/or related Education Program. Preferred Experience: Operation and maintenance of high pressure boilers and related equipment. Fundamental knowledge of industrial plant chilled water
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The Department of Electrical and Computer Engineering at the University of Virginia is accepting applications for research scientist position for machine learning methods for magnetic resonance