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at various points in a subcritical model reactor operating at near-zero power and driven by an external high-intensity, high-reliability neutron source; 2) Extending the previous results to a power ADS loaded
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proceed with the definitionand numerical implementation of the models for the simulation of the magnetic, electrical, thermal, and mechanical behavior of these devices. Appropriate experimental setups will
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field modeling of brittle fracture: Part I—Theory and simulations, Journal of the Mechanics and Physics of Solids, Volume 121, 2018, Pages 81-98, https://doi.org/10.1016/j.jmps.2018.07.010. [2] Lamia
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fields in cosmic voids and filaments. The candidate will reduce model uncertainties by producing new large cosmological simulations of the magnetic outputs from galaxies in the ENZO code, which will test
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thermodynamic cycles by combining two complementary approaches: - Generative models derived from artificial intelligence, capable of proposing new process architectures; - Superstructure-based optimization
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) The overall following data and analyses of the different physical effects (orbital vs. Spin contribution) will be accompanied by the development of advanced theory/model/numerical simulations and possibly DFT
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). Knowledge of complex network modelling, omics data analysis or computational simulation. Research FieldOther Internal Application form(s) needed Perfil. .pdf English (606.79 KB - PDF) Download Additional
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analysis, including handling complex databases Essential Application/Interview Proficiency in computational modelling software and tools being used for simulation of non-invasive brain simulations Essential
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | about 14 hours 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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%). You will work at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model