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to different aspects: - conception, mplementation and optimization of the optical experimental device - programming - characterization on different samples - sample preparation - writing of articles
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
optimizing complex systems across a wide range of domains, from industrial manufacturing and energy to environmental monitoring and healthcare. The Engineering Digital Twin EDT program , funded by the France
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desorption methods; Applying and optimizing a minimally intrusive vapor-phase isotopic exchange method (²H/¹H and/or ³H/¹H) to quantify the accessibility of reactive sites within insoluble organic matter
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dedicated, low-energy electron beam ion trap (EBIT) optimized for the production of highly charged ions of light nuclei that remain beyond the reach of storage rings. This EBIT, a central element of the
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(bbγγ) channels. In the classical HH(bbγγ) analysis, the H(γγ) channel is treated as a major background process for the di-Higgs channel. A joint analysis of both modes would optimize the overall
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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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optimized physical and mechanical properties, in particular for energy-related (e.g., solar cell), aerospace and nuclear applications, where materials are exposed to ion irradiation. Although the effects
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understanding and enable the optimization of catalysts and experimental conditions. More specifically, the student selected for this position will be tasked with mapping the MHAT reactions of alkenes by
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approach. WP1 dealing with the elaboration, characterization and optimization of Cu/CeO2-TiO2 photocatalytic systems, will be mainly performed at IS2M (Mulhouse) and WP2 focused on the evaluation of gas
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of Cognitive Engineering and Decision Making, Volume 17, Issue 1, 2022. [2] A. Muzahid et al. “Survey on Human-Vehicle Interactions and AI Collaboration for Optimal Decision-Making in Automated Driving”, arXiv