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to power and energy systems • Proficiency in Python, with experience using optimization frameworks such as Pyomo or Linopy and optimization solvers • Knowledge of advanced optimization and decomposition
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of the tissue using water-soluble clearing and refractive index matching media, and evaluating the benefits of this approach for three-dimensional imaging. The first year of the project will focus on optimizing
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programming tools (Matlab, Python, C++) is essential, and knowledge of NMR/MRI would be a valuable asset. Mechanistic insights and optimization of synchronized respiratory stimulation as a therapeutic
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knowledge gap stemming from the broader difficulty of coupling directly to azimuthal waves with large orbital indices. The goal of this internship is to study these hidden azimuthal modes using a scanning NV
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
Will Gain from This PhD This PhD offers the opportunity to: Develop highly sought-after skills in knowledge engineering, semantics alignment, and collaborative innovation. Collaborate with leading
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crack initiation and propagation; Development and validation of a digital twin with an appropriate level of maturity; Proposal and evaluation of new cluster architectures; Validation of optimized
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understanding of microstructure-property relationships in materials systems in the presence of different stimuli close to operational conditions. Such knowledge is crucial for designing advanced materials with
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capable of automatically selecting the simulation strategy best suited to a given prediction objective, while optimizing the trade-off between accuracy and computational cost. The work will build on multi
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: • To design and optimize an electrolyzer that simultaneously promotes mass transfer, contaminant degradation, and gas recovery; • Study the influence of operating parameters (current density, reactor geometry