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- MOHAMMED VI POLYTECHNIC UNIVERSITY
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Field
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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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analysis by integrating diverse datasets (e.g., in situ observations, remote sensing products, model simulations) to inform model development, calibration, and validation. Collaborate with a
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measurements of indoor environmental quality (IEQ), energy simulations, and machine learning modelling; (b) strong analytical and problem-solving skills, with the ability to conduct research independently
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their scales, exploring parameter space for vortex behaviour using theory and idealised model simulations, testing the relevance of the new paradigm using case studies observed using during the NERC
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familiarity with at least one of: DFT workflows, Wannier/TB model building, or quantum-transport simulations; willingness to become hands-on across the stack. Comfortable with Linux/HPC, job schedulers, and
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or liquid chromatography, mass spectrometry, optical diagnostics, lasers, IR-UV-Vis spectrometry - Measurements in atmospheric simulation chambers, in reactors coupled with laser-induced fluorescence
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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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and implemented in Fenics to: - Identify the mechanical properties of collagen hydrogels, depending on their manufacturing conditions, based on experimental data. - Improve these models to include
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to the Lab’s broader effort in CH4 and CO2 utilization R&D. The role will require the individual to work with personnel that perform machine learning and molecular simulations and electrochemical device testing