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on solubility, dissolution kinetics, and microbial influences. Your work will refine global carbon cycle models, enhance CO₂ sequestration understanding, and position you at the forefront of ocean
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for biomarkers in 7T images. - Development of artificial intelligence algorithms and models for the processing and analysis of MRI images/spectra, focusing on the detection of tumor tissue and the quantification
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porous media (imbibition, wetting, flow, etc.). The approach will be essentially experimental, combining model debinding tests on various specimens with characterizations. • Determine the main mechanisms
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Infrastructure? No Offer Description The postdoctoral researcher will contribute to the ANR-funded Pi-CANTHERM project, which aims to design, model, and predict the performance of new n‑type organic thermoelectric
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sample preparation, electrochemistry, or quantum modelling (DFT) would be an asset. The recruited researcher is expected to demonstrate a strong ability to work independently (critical thinking, literature
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research and will contribute to the research work of LEMTA. The work will be of experimental and/or numerical nature, relying on state-of-the art laboratory equipment and numerical modelling resources
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extended complexes) The application to various models of MHD and flows in porous media The numerical analysis of the schemes The development of the computational kernel of the NEMESIS software library
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and process behavioral and electrophysiological data • Model behavior based on diffusion models and make explicit link with neurophysiological data • Conduct detailled statistical analysis • Write
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will be hosted at LCPMR (Sorbonne Université, Paris), in a dynamic scientific environment internationally recognized for its expertise in attoscience, numerical methods, and modeling. The EPAD project
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primarily focus on one or more of these parts. The successful candidate will develop numerical tools and/or theoretical models to model and simulate the behavior of a group of agents capable of chemical