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imaging techniques) to the resulting visual appearance (measured with appearance-based methods). The post-doc will be supervised by Bilge SAYIM at the École Normale Supérieure (ENS), Université PSL, within
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focuses on the transfer of ionic and electronic charges at the interface of materials, which are the cause of many limitations and degradation processes in batteries. The goal is to characterize the state
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, including: - Cell culture (Biosafety Level 1 and 2) - Histology (tissue processing automaton, microtomes, cryostats) - Pulmonary function analysis (invasive and non-invasive plethysmographs) - Animal
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security, artificial intelligence, image and text processing, microelectronics, etc. The laboratory is particularly involved in AI research, notably developing work on generative models to accelerate
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processing, involving machine learning techniques, as well as active participation in data collection from the detectors deployed on site. - Analysis of particle physics data applied to muography: filtering
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time in a cyanobacterium, challenging the usual paradigm according to which cyanobacteria biomineralise CaCO3 extracellularly as an indirect by-product of photosynthesis (Couradeau et al.; 0.1126/science
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experiments and numerical simulations and will be divided into three parts: Microstructure: 1.1. Experimental Characterization: Using X-ray tomography, image analysis with conventional tools or deep learning
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scenarios for possible « hydrogen » systems in the basin. This will be done using a prototype version of the TemisFlow commercial software developed by IFPEN. - The first part of the work will consist of a