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Field
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Kleitz at the University of Vienna mainly focusses on the development of nanoporous materials, their characterization, and their applications in numerous fields, such as catalysis, adsorption, bio- and
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live in. Your role Research related to the following areas: Mathematical statistics, Machine Learning, High-dimensional statistics, Robust estimation methods, Probabilistic foundations of mathematical
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-method study of human cultural adaptation to environmental challenges with application to invasive plants and tick-borne disease threats among woodland owners with supervision from Dr. Waring and in
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://www.chalmers.se/math/ At the division of Applied Mathematics and Statistics we conduct research within probability theory and its applications, the theory and implementation of finite element methods, inverse wave
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lattice field theory and numerical methods, with experience in HPC programming (e.g., C++, Python, MPI, OpenMP, CUDA) and parallel computing environments. - Experience in performance analysis, debugging
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backgrounds and lead annual fieldwork activities for sample collection. Opportunities to travel to conferences and project meetings are also available. This position provides numerous opportunities
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to reduce the complexity in simulating lake physical dynamics at scale. Borrowing from numerical methods used to design wind turbines and understand turbulent combustion in jet engines, this research aims
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Sciences at Princeton University. The research will be to conduct numerical studies for non-local flow-driven magnetized plasma instabilities and their associated nonlinear transport in astrophysical and
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Do you have experience with modelling structures subjected to dynamic loading? Are you interested in data-driven methods for modelling applied loading? Are you eager to share your knowledge within
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be to develop high fidelity simulations and/or algorithms to enable Bragg coherent diDraction imaging. We expect x-ray ptychography and coded aperture methods to play a fundamental role in creating a