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Can We Teach AI to Outsmart Humans in the Werewolf Game—Without Changing the AI Itself? Large Language Models (LLMs) have dazzled us with their ability to converse, code, and create—but they still
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computational model to capture the complex transport of gases, liquids, and charges in these porous structures, including the complex interfaces between them. Insights from the model will directly guide the
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simulations in 3D MHD of the propagation of solar jets, in close connection with solar and in-situ observations. This should lead to the development of the next generation of solar jet propagation models, from
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similar languages) Experience with large-scale neural network simulations Experience with analysing large-scale neural recordings Familiarity with neuroanatomy and neurophysiology Knowledge of dynamical
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affect ignition behaviour. You’ll use advanced tools such as chemical kinetic modelling, multi-dimensional CFD simulations, and collaborate closely with experimental researchers. You will receive
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neuroscience and data analysis Proficiency in programming (e.g., Python, MATLAB, and similar languages) Experience with large-scale neural network simulations Experience with analysing large-scale neural
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student will develop novel, generalized models of doping in semiconductors, based on the drift-diffusion framework of Fluxim’s simulation software Setfos. The PhD project involves the following
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, antennas, and electromagnetic metasurfaces. The computer-aided simulation of electromagnetic fields is critical in the design of most computing and communications devices, such as high-speed interconnects in
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, there is no consensus on the adsorption mechanisms of these molecules on the metallic surfaces. In this PhD project we will use state-of-art molecular simulation methods [2,3] to clarify the adsorption and
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new business models based on distributed storage and dynamic sharing coefficients, integrated into a regulatory sandbox and real-world test environment. Main tasks: Create algorithms to maximize