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heterogeneous cyber data. While traditional techniques such as Principal Component Analysis (PCA), clustering, and autoencoders help reduce dimensionality and improve detection performance, they remain
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learning assistants, they deprive learners of a key element for a successful learning experience: collaboration with teachers and among learners [6]. A second aspect is often overlooked in current research
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. This group has been performing adsorptive studies using various biomaterials, especially waste-based materials, and their characterization for wide-ranging applications such as the removal of heavy metal ions
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visible in the image²,³. Multispectral imaging (MSI) overcomes these limitations: it provides quantitative access to retinal physiology (oxygenation, tissue composition) through fine spectral analysis⁴. It
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physics and applied mathematics, with at least one specialization in one of these two fields and a strong interest in the other. While the experimental component remains important, it is wellmanaged
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future networks (5G/6G), o embedded systems and IoT, o interdisciplinary research topics. Work Plan The PhD work will be structured around four main phases: Analysis and Modeling o analysis of use cases, o
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Numerical Study of Soil Remediation by Thermal Desorption with a Focus on Industrial Decarbonization
selection of appropriate desorption processes. Finally, a techno-economic analysis will be conducted to assess the operational feasibility of implementing the treatment at Séché Environnement sites. Research
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-human interaction, in particular the ability to anticipate. A first challenge is the multimodal analysis of human interactions, that includes not only the automatic assimilation of the physical movements
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PyTorch. ✔️ You have a good knowledge of linear algebra and statistics. ✔️ You have good listening, analysis and synthesis skills, and are curious and open-minded. ✔️ You are adaptable, autonomous, rigorous
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definition of data–model independence • Information-theoretic bounds (mutual information, stability) • Analysis of privacy–utility trade-offs 2. Attack Modeling and Empirical Analysis • Implementation and