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the network vertices act independently by learning from their local observations. You will mathematically analyze the algorithms on random graph models and implement them on large real-life networks
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in fluid dynamics, mechanical engineering, computational physics, applied physics, mathematics, geophysics, or related subject areas. Proficiency in programming languages such as Fortran, C/C++, MATLAB
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Specific Requirements You hold an MSc in Statistics, Mathematics, Artificial Intelligence, or a closely related discipline; You have a strong background in quantitative modeling enabling the development
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combining methodologies from computational fluid dynamics, solid mechanics, and mathematical optimization. You will collaborate with both local and international partners (this includes clinical, experimental
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is to benefit science, and to contribute to the major societal challenges of the future. The research carried out at the Faculty of Science is diverse, ranging from Mathematics, Information science