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Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO | Grenoble, Rhone Alpes | France | 3 months ago
Post-doctoral Position In Medical Image Processing The Computer-Assisted Medical Interventions (CAMI) team at the TIMC laboratory (Grenoble, France) is seeking a highly motivated postdoctoral researcher
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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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explainable. Our team builds upon over 20 years of expertise in image processing algorithm research and more than 15 years of experience in developing open-source software for image processing and digital art
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conduct in vivo experiments to investigate retinal neurovascular dynamics using the AO-RSO system; Develop or adapt high-speed image acquisition and processing methods for simultaneous measurement
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project on the release of hormones, neuropeptides, and neurotransmitters by exocytosis, which is mediated by a vesicular fusion process whose mechanisms are well established. However, the mechanisms
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, involving expertise in optics, electronics, image and data processing, chemistry, and biology. With the support of several European funding programs, the team is building a data science and machine learning
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signal/image processing, computer science, applied mathematics, or a related field, obtained less than 3 years before the date of hire. Essential skills, knowledge and experience: Excellent command
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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 sensors, such as the
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of Research ExperienceNone Additional Information Eligibility criteria - PhD in Medical Imaging, Biomedical Engineering, Signal Processing, or a related field. - Strong expertise in MRI physics, preferably in
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develops microfluidics devices for non-destructive single-cell imaging in controlled conditions that, combined with molecular genetic methods, allow to monitor the dynamics of these processes at the single