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innovative methods for processing and analyzing 7Tesla MRI images of different modalities and formats (NIFTI, DICOM, etc.) using machine learning and artificial intelligence techniques. These methods will be
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of the variability and uncertainty of simulated outputs • an explicit quantification of prediction error • an interpretable and controllable structure (e.g., Gaussian processes, …) 2. Model industrial system
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input fields and then regress on the target variables in the embedding space. However, many challenges remain to be solved with this approach (regarding the use of CNNs vs Vision transformers
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charge‑transport properties. • Familiarity with codes such as Gaussian, VASP, CRYSTAL, Quantum ESPRESSO, or equivalent. • Ability to collaborate in an interdisciplinary environment and to communicate
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involved during capillary debinding through the use of specimens and model tests • Understand the influence of processing parameters on debinding mechanisms and kinetics • Determine the influence of
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Description Conduct a part of the ANR MetaTime (setting-up experiments, acquisition and processing of data, writing scientific reports) • Perform a review of the existing litterature on the topics • Acquire
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focuses on understanding magmatic processes, examining everything from the structure of the deep mantle to surface volcanic activity. The Laboratory consists of about 60 tenured researchers. The research
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dissipation processes driven by waves in the ocean The project involves numerical simulations of various atmospheric and oceanic conditions using large eddy simulations (LES), followed by parameter calibration
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, the postdoctoral fellow will seek to elucidate the fundamental processes leading to the formation of the "Solid Electrolyte Interphase" (SEI) in batteries. This will include understanding the precipitation of
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structural health monitoring of structures immersed in heavy fluids, by continuing to develop the “Modal Strain Energy” and “Matched Field Processing” methods for detecting and locating a potential defect in