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will be analyzed considering various scenarios. To this end, agents having similar characteristics to the entities (job seekers and firms) will be defined in an agent-based model, which will simulate
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inverter topologies (e.g. Dual inverter, 4 bridge inverter) with modern semiconductor devices (GaN, SiC) The aim is to implement own designed algorithms in a signal processor and simulation environment
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Translational Neuroimaging of Neurogenetic Disorders DPhil (PhD) Department of Psychiatry, University of Oxford Start: October 2026 Neurogenetic disorders, including aneuploidies and recurrent copy
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-Test-Analyze (DMTA) cycle, infusing scientific automation with foundation models, multi-agent systems, and robotics to make scientific discovery intelligent, autonomous, and fast. We're seeking a
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and industrial processes, addressing questions of advanced numerical modelling and simulation, measurement techniques, robust sensors, data analysis for experiments and real-world monitoring
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overall robustness and maintainability, the target is to explore the use of physics-based simulation tools, such as Drake. The main benefits considered are the ability to model contact dynamics, validate
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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | about 5 hours ago
absorption. Developing fast spectral radiance simulation techniques and implementing the observational system simulation experiment (OSSE) based on GISS climate model, which will be applied to research
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you? Then join our accomplished team! Where to apply Website https://iventajobdata.eu/bestmedia/img/2235821/1889876/cl/ba24755482c066846a2ba… Requirements Specific Requirements About the team: This is
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learning environment. The instructor maintains accurate records, assists with program development and recruitment, and models the professional standards expected in the nursing field. This position is funded
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agroecosystem model simulations. The successful candidate will play a key role in developing robust landscape-scale digital twins and advancing data assimilation techniques for agricultural and environmental