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to the industrial recovery and reuse of these critical elements. More specifically, the proposed mission will explore two avenues: - optimization of Rh solubilization during dissolution of model
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/Qualifications - Automation or applied mathematics background, with a strong interest in physical models and numerical method - Analysis of partial differential equations, variational approach, Bayesian estimation
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miscible) is approached. Moreover, as the correlation length diverges, fluctuations become increasingly important and the physics of these fluctuations has to be considered and modelled near the liquid
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: - using experimental data to develop a kinetic model; - modelling the pilot-scale reactor for plasma-assisted NH3 synthesis; - intensifying the reactor and extrapolating to develop the industrial-scale
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companies will also be studied. The optimization model will encompass the modeling and implementation of several technologies, including steam networks, hybrid power systems, and auxiliary and storage
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University, is recognized for its expertise in artificial intelligence and formal methods In this stimulating academic context, we will focus on the problem of explainability of artificial intelligence models
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will involve (but not be limited to) applying sophisticated mouse genetic models of cancer and conditional gene targeting, single-cell RNA-seq, spectral flow cytometry, multiplex imaging and spatial
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, cell culture, structural modelling and optogenetics Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR8197-VALHER-211/Candidater.aspx Requirements Research FieldNeurosciencesEducation
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of transportation and energy. Its experimental and numerical modeling activities focus on various complex and multiphysical flows, including turbulence, two-phase flows, combustion, and thermoacoustics. Research
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involves developing state-of-the-art methods for image segmentation, detection, classification, predictive modelling, and image enhancement. We aim to build more trustworthy and robust AI models that can