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responsibility of developing predictive tools based on machine learning for the analysis and interpretation of Raman vibrational spectra applied to battery materials. The successful candidate will design and
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focused on deep-phenotyping of individuals with autism and controls including brain imaging (MRI, fMRI, DTI and EEG) and a battery of cognitive tests. Our group is currently developing new methods
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the Electrode/Electrolyte Interfaces via Operando Piezoelectric SENSing) project, which aims to develop a new-generation analytical tool for studying electrode-electrolyte interfaces in rechargeable batteries
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the application of the university’s strategy. This position is available within the Faculty of Science and Engineering: http://sciences.sorbonne-universite.fr Within Sorbonne University, the Faculty of Science and
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, worn-out battery) lead to repurchases, some replacements are also due to software issues: slowness, feeling of heaviness, compatibility issues, OS or applications that are no longer updated, etc. As part
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sustainable operation and thereby addressing the issue of limited battery capacity. Missions : The main responsibility will be to implement the experimental testbed already developed at XLIM, used to validate