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to unravel the atmospheric importance of this interfacial chemistry by means of (i) laboratory-based investigations, (ii) field observations and (iii) modelling. These activities will take place in the frame
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of various existing datasets (picking files of local earthquakes and shots), recording of P-waves converted to S-waves on OBS, construction of an a priori model based on available tomographic grids and
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particular the hypothesis that the models applied to convert ALS measurements into above-ground biomass are transferable to all Central African forest landscapes, and the hypothesis that the BIOMASS satellite
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and analyzed. The results will inform the development of new models that describe how seafloor spreading operates on short time scales. ⁃ Perform statistical analyses (assessing distributions
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genetics - Coding eco-evolutionary models - Data analysis - Interpreting and exploiting results - Writing scientific publications - Oral presentations of results - Working as a team and independently Website
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The postdoctoral fellow will participate in the PostGenAI@Paris AI Cluster (ANR) project at Sorbonne University, and more specifically in the "AI-Augmented Multiscale Modeling for Energy Storage" sub-project, whose
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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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the measurements to be performed. - Determine the isotopic compositions (δ13C and δ18O) of ostracod larval capsules using IRMS. • Organize the dataset: - Verify and update the age models of the cores. - Integrate
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the aim of identifying relevant topological invariants to characterize the underlying dynamics and guide the selection of appropriate reduced models. - Adapt and implement existing topological tools
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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