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development techniques (numerical methods, solution algorithms, programming models, and software) at scale (large processor/node counts). Experience with use of artificial intelligence and machine learning in
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be involved in the three-year project “High Dimensional Hierarchical Optimization methods for Machine Learning and Stochastic Optimal Control”. Background or expertise in one or more of the following
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Machinery Design. Other requirements to consider Teamwork. Specific Requirements Educational Requirements: Fluid Mechanics. Advanced Mechanical Engineering (or similar). Numerical Methods in Fluid Systems and
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NAnoparticles by combining experimental and numerical approaches ), funded in 2024 by ANR – The French National Research Agency. Nanoparticle (NP) synthesis is a viable way of pursuing the production of next
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magnetometry), underwater research, as well as archaeometry (isotopic methods, bioarchaeology, histology). Numerous research projects are conducted at the Faculty of Archaeology, including those funded by
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of Applied/Computational Mathematics. Research topics of interest include numerical methods for scientific machine learning and AI, and their applications to various science and engineering disciplines
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of the fabricated fibers within optical networks. - Design of innovative hollow-core fiber structures using the finite element method. - Fabrication of specific optical fibers on a fiber drawing tower. - Linear
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(excavations and surface surveys), geophysical methods (including magnetometry), underwater research, as well as archaeometry (isotopic methods, bioarchaeology, histology). Numerous research projects
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skills 6. Competence in spoken and written English 7. Ability to work in a team Desirable criteria 1. Numerical skills, such as: Monte Carlo methods, Density Matrix Renormalisation Group
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analytical and numerical methods for the investigation of novel quantum magnetic states of matter in frustrated spin systems. Methods to be applied include, e.g., field theory approaches, exact diagonalization