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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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to solve this issue. Indeed, there is growing evidence that thermal imaging could serve as a tool for measuring emotions in a non-invasive, contact-free way, that does not require verbal communication
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, computer science (medical image processing), medical physics. Computer skills: Python, C++ (ITK, RTK). Languages: English required, French optional. Website for additional job details https://emploi.cnrs.fr/Offres
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. The institute offers a multidisciplinary environment that bridges fundamental discoveries with applied preclinical research. In partnership with IMATHERA (Preclinical Imaging and Radiotherapy Platform
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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
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interacts with the Quantitative Imaging Platform of Villefranche (PIQv; https://sites.google.com/view/piqv ), which oversees the operation of the tools that the team develops. Those tools include imaging
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computational research. In particular: • A high-quality imaging platform • A dedicated biocomputing hub that guarantees reliable data storage, management, and advanced analytical capacity. Our laboratory is
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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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focuses on the transfer of ionic and electronic charges at the interface of materials, which are the cause of many limitations and degradation processes in batteries. The goal is to characterize the state
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cellular biophysics -Backround in microfluidics -Background in image processing Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR5588-CHAMIS-012/Default.aspx Work Location(s) Number