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to the identification of host and microbial metabolites and their pathways involved in metabolic diseases, including delineation of their genomic, metagenomic and environmental determinants. The objective is to develop a
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and to characterize interactions with fire regimes. Ultimately, these results will also contribute to a combined paleo-modeling approach at the core of the RETROPEST project (https://anr.fr/Projet-ANR
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) ● Developing multiplexed RNA-FISH assays for cell type identification ● Quantifying nuclear organization features (3D chromatin structure, topology, chromatin state) ● Analyzing imaging datasets using
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interfaces in batteries by the identification of chemical species. Efforts are still required to design reliable operando cells for XPS investigation, as most of battery limitations originate from electrode
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implement and train neural network architectures, including Physics-Informed Neural Networks (PINNs), in order to integrate physical constraints into the learning process and improve the identification and
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-rich environments. The candidate will participate in field sampling, species identification, and laboratory cultivation of nematodes from extreme habitats. The candidate will also take part in molecular
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, DSC, TGA, FTIR, mechanical and rheological properties, etc.) - Development of waterborne polyurethane dispersions (PUDs). - Identification of the best formulations meeting specifications
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matter gravity simulators, enabling the identification of exotic properties of relativistic materials. Use of various theoretical methods to study the effects of field theory properties in curved spacetime
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effects on the performance of an integrated circuit (IC). 2. Identification of aging and/or performance signatures that can be extracted using non-invasive and non-destructive methods, such as imaging
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properties in order to hinder their presence. Goal of the project: • Identification of the intermediate species • Understanding their synthesis mechanisms and parameters during the fuel cycle • Presenting a