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to complementary physical properties of thermal, combustion and detonation. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UPR3346-NADMAA-156/Candidater.aspx Requirements Research
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PhD MSCA - Acoustic and Ultrasound-based Predictive Maintenance Systems for Industrial Equipment Power converters are essential in numerous applications such as industry, photovoltaic systems
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 15 days ago
) at the IT4Innovations, in the Material Design group of Dr. Dominik Legut within the Modeling of Nanotechnology Lab, is open to applicants for the SPIN DYNAMICAL CALCULATIONS of the topics of Czech Science Foundation’s
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
code development or open-source contributions, polymer chemistry, and mathematics, modeling, or numerical methods. An established record of research productivity is highly desired. Special Physical
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optimization of laser deposition coating processes using combined wire and powder feed, including numerical simulation of laser modelling, and process parameter optimization. Legislation and regulations: Law Nº
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Your Job: This PhD project focuses on modelling and simulating future gas grids, exploring transformation pathways, and developing cross-sectoral simulation frameworks to support informed decision
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 26 days ago
-tolerance to the insulin producing beta cells, and 2) Development of immunotherapies for T1D. The work makes use of several genetically manipulated mouse models of T1D, as well as humanized mouse models, and
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. The successful candidate will contribute to the development of predictive numerical models and experimentally validated designs for intricate mechanical assemblies, deployable structures, compliant mechanisms, and
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trips, plus an elective course. Examples of elective courses could include aqueous geochemistry, geomorphology, soils, glaciology, GIS, or numerical modeling. We are seeking candidates who can demonstrate
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datasets, modelling approaches, and performance metrics; develop physics-informed and data-efficient machine learning models to predict sorbent behaviour from sparse and multi-modal experimental data; and