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candidate will be responsible for the full range of activities related to the development, testing, and evaluation of the learning models. They will also receive support from LOA experts for the execution
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(Probability, Statistics and Modeling Laboratory, CNRS-Université de Lorraine), EDF (Electricité de France), and Fives-Prosim. This doctoral program focuses on generative models for energy cycles. Its main
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of Communities team and interact with its members. The modeling work will also involve collaborations with researchers from CEFE (Montpellier), BIOGECO (Bordeaux), and forest management partners (ONF). Our little
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of the landscape over time. The LANDIS-II forest landscape disturbance and succession model will be used to perform simulations based on palaeoecological data. The student will collaborate with project researchers
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pressure and temperature levels; - Validate the numerical model of the complete system by comparison with experimental data; - Identify improvement strategies for performance and system robustness. Work
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the TRACCS research program (Transforming Climate Modeling for Climate Services, https://climeri-france.fr/pepr-traccs/ ), which brings together the French climate modeling community. Its activities cover
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' genomes model. This 'two-speed' genome model stipulates that the genome is composed of two compartments with different architecture, content and speed of evolution. The first compartment, composed of core
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complementary expertise, using both space and ground-based observations of the solar atmosphere, in-situ measurements from heliospheric probes, in synergy with a complete numerical modeling of the generation and
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turbulent plasmas and by phenomenological models. The overarching goal of this ambitious programme is to describe the acceleration process across length scales, in the turbulent flow, in the inner jet and in
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metabolism in type I interferonopathies within tissues. Using mouse models of these diseases, we will analyze how metabolic alterations contribute to inflammation and tissue damage. We will generate lipidomic