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for students with BSc degree with reference number BI|2026/880 under the scope of the Projet SALVE: Securing Artificial Language Models Against Vulnerability Encoding (2024.14936.PEX), funded by Fundação para a
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 3 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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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 6 days ago
from the surface or the coast into the interior ocean Test Lagrangian tools and contribute to their development Conduct model simulations covering the recent decades and the future Present project
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computational modeling and simulation to evaluate how data center demand affects electric grid reliability, resilience, and operational flexibility under various growth and climate scenarios. • Life-Cycle and
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 14 days ago
intelligence is growing at a fast pace, the bulk of the world's computing power remains targeted at modeling and predicting physical phenomena, such as climate models, weather forecasting, or nuclear physics
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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funded through the Research Ireland Frontiers project "Nanoelectronic Quantum Simulators". The project will involve studying quantum circuits as a platform for analogue simulation of fundamental models
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systems. These models will be part of a multicellular modelling and simulation framework being developed as part of the Australian Research Council's (ARC) Discovery Project "Bridging biological boundaries
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induced seismicity. Current models remain limited by the scarcity, heterogeneity, and noise of available data, as well as by incomplete knowledge of the subsurface. Physics-Informed Neural Networks (PINNs
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and other complex fluids using molecular simulations. In order to make these simulations more computationally feasible, development of coarse-grained models and new Monte Carlo or molecular dynamics