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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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(energy, spatial resolution, stability) Analysis and interpretation of experimental data Preparation of scientific publications and presentations at conferences Interaction with academic and industrial
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metastability processes under different operating conditions (dark, illumination, electrical bias); Spatial analysis of performance inhomogeneities and degradation mechanisms using optical and electrical mapping
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shift a critical part of the spatial and photophysical information into the temporal domain, in order to drastically reduce the number of photons and the acquisition time required for image reconstruction
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, the recruited researcher will contribute to the development of a novel time-resolved fluorescence lifetime measurement approach, in close connection with methods based on single-molecule brightness analysis
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molecules using site-specific conjugation strategies. - Development of DNA origami scaffolds to spatially organize and orient proteins for structural studies by single-particle Cryo-Electron Microscopy
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Mohammed (Maurice Halbwachs Center, CNRS). This research project is structured around five axes: analysis of police and court records; sociology of the anti-drug police enforcement; analysis of the social
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tools, Earth foundation models, and a good working knowledge of modeling approaches in ecology. In particular, we are looking for someone interested in developing hyperspectral data analysis pipelines and
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of ASICs dedicated to the readout of AC-LGAD (Alternating Current coupled Low-Gain Avalanche Diode) sensors, capable of very good timing (~30 ps) and spatial (~20 um) resolutions, which will be exploited by