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learning (e.g., deep learning, optimization, or learning theory) Programming skills in Python and experience with scientific computing (e.g., NumPy, SciPy, PyTorch) Experience with numerical
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complexity required to represent PVD-functionalized electrodes without unnecessarily increasing computational cost. The work will combine fundamental modelling, numerical simulation and experimental
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toward the implementation of CCUS through process optimization, the development of LCA/TEA assessment tools, and technology deployment scenarios. https://unit.aist.go.jp/ccus/groups/cart.html * details of
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knowledge of iterative learning control theory with applications to industrial systems Excellent foundation in linear algebra, numerical methods, optimization, and control theory Background in online
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accounting for the available and expected energy resources. The research will combine numerical modelling, control development, optimization, and experimental validation. The work will build on existing
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simulator and training libraries. Good foundation in linear algebra, numerical methods, optimization, and control theory. An excellent knowledge (written/oral) of English is a must. Knowledge of German
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. The primary objective is to simulate quantum devices such as the resonant tunneling diode. This requires a careful analysis of spectral properties and the development of WKB-type numerical schemes
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Mathematics, Economics, or a related quantitative discipline, completed by the appointment date. Demonstrated research experience in stochastic or dynamic optimization, online learning or sequential
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process modelling, simulation, and optimization. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR7274-BOUBEL-004/Default.aspx Requirements Research Field Engineering Education Level PhD or
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Mathjobs.org | 24 days ago
analysis, numerical analysis, sampling methods, optimization, scientific computing, or related areas, together with research experience in at least one class of modern generative models, are