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networks (5G and WiFi 7 and their evolutions) in terms of architecture, protocols, and optimization. These networks benefit from new technologies and approaches, such as virtualization and AI, to make them
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physics is especially interesting due to the presence of exotic excitations, potentially non-Abelian. The TensQHE project aims to develop modern numerical tools based on tensor networks, within an open
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Pasteur center, in Paris (France). We are seeking an outstanding, highly motivated advanced scientist in molecular biology and neuroscience for projects on gene regulation and gene regulatory networks with
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data from measurement and observation networks, as well as snow testing protocols, to provide access to a larger, harmonized information system on both sides of the border; Mutual training and
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over the course of the project. References: - Deneu B et al (2021) Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment. PLoS Comput
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- Design pilot and data collection of MEEG and behavioral experiments with Psychtoolbox, JsPsych, Pavlovia - Univarate and multivariete analysis (RSA, encoding and decoding models) of MEEG data at sensor and
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for the High-Luminosity LHC. Our primary responsibility is the integration of double-sided silicon sensors onto mechanical support structures (ladders), including the associated electrical, optical, and cooling
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, robustness under varying turbulence, and autonomy for distributed systems. To address this, the group integrates Artificial Intelligence into AO control loops, using deep learning to handle sensor
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analysis for more geometries and with a reduced number of sensors - Implementation of the MSE method on a cylindrical structure immersed in water and sensitivity analysis - Algorithmic and experimental
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) * electromagnetic design of device using soft-ware such as comsol *clean room fabrication using both optical and e beam lithography *Optoelectronic characterization of infrared sensor (I-V, photocurrent spectrum