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a multidisciplinary problem centered around computational mechanics and engineering, potentially involving (i) multiphysics problems, (ii) multiscale methods, (iii) uncertainty quantification and (iv
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University of California, San Francisco | San Francisco, California | United States | about 5 hours ago
project, forming relationships and applying standardized and proven problem-solving methods to actively resolve upstream and midstream challenges through all steps of the research process. The duties may
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that synchronisation between storm waves and elevated water levels can stabilise certain Baltic Sea beaches, challenging the traditional “cut and fill” concept. Despite numerous site-specific studies, there remains a
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approximation algorithm, using linear programming methods. Over the next years, the project will grow to a collaborate team of 4-5 PhD students and Postdocs. The successful candidate will work directly with the
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
of the following areas: Large-deformation numerical modeling (e.g., Coupled Eulerian-Lagrangian (CEL), Material Point Method (MPM), or advanced Finite Element Methods). Physical modeling of tunnel
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of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation, numerical methods
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particular in numerical methods for CFD and their programming. Other academic merits as participation in congresses or research workshops, awards, research contracts and collaboration scholarships will be
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and health. The lab conducts method-driven research in natural language processing (NLP) and artificial intelligence (AI), with an emphasis on LLM reasoning, uncertainty quantification, interpretability
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series. Linear Algebra: Matrices, vector spaces, linear systems, eigenvalues. Numerical Methods: Numerical solution techniques for material modeling. Functional Analysis: Hilbert spaces and operators
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at the intersection of numerical linear algebra and advanced HPC. The candidate will join an international environment, with opportunities to collaborate with experts from the USA, and KAUST and publish in top-tier