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and output databases; deployment of methods and tools for data acquisition and visualization; * AI/Machine Learning/Deep learning techniques for model input and output data analysis and production, in
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. The approach used relies on developing machine-learning interatomic potentials based on ab initio calculations, which are then employed to perform large-scale classical molecular dynamics simulations. However
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experimentation with innovative modeling, data analysis and machine learning/AI techniques. 1 - Global Energy-Economy-Environment Systems Modelling Your main duty is to contribute to our collection of linear
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experts, offering a framework conducive to learning and collaboration. You will have access to state-of-the-art equipment and first-rate research resources to carry out your assignments. Main goals (1
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. Moyens / Méthodes / Logiciels Matlab, Python, Signal processing, Digital communications Profil du candidat Required skills: •Signal processing and digital communication •MATLAB/Python •Proficient in using
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-renowned research environment. Our teams are made up of passionate and dedicated experts, providing a framework conducive to learning and collaboration. You will have access to state-of-the-art equipment and
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. Our teams are made up of passionate and dedicated experts, offering a framework conducive to learning and collaboration. You will have access to state-of-the-art equipment and first-rate research
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The detection of out-of-distribution (OoD) samples is crucial for deploying deep learning (DL) models in real-world scenarios. OoD samples pose a challenge to DL models as they are not represented
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and particles, while the latter can induce radial redistribution or losses of EPs, limiting their contribution to plasma heating. Traditionally, these processes have been studied separately, assuming
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good understanding of matrix algebra • Good understanding of RF power amplifier design (Class of operation, loadline theory, loadpull…) • Good understanding of semiconductor process such as CMOS, BiCMOS