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microscopy techniques (e.g., spinning-disk confocal microscopy, light-sheet microscopy) analysis of large imaging datasets using advanced image processing and segmentation methods computational and statistical
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(immunohistochemistry/fluorescence, in situ hybridization) and emerging spatial transcriptomic technologies coupled to a robust image capture and semi-automated image segmentation pipeline to enable the large-scale
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7 Mar 2026 Job Information Organisation/Company CNRS Department Laboratoire d'informatique en image et systèmes d'information Research Field Physics Researcher Profile First Stage Researcher (R1
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for quality and proper format. Makes notation when images are to be repeated, and the proper technical factors needed for correction. Provides patient education prior to, during, and subsequent to the procedure
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). Proven experience in scientific programming and numerical computing (MATLAB, Python, or C/C++), including implementation of reconstruction algorithms and image processing pipelines. Experience with
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all aspects of the MRI imaging functions, and providing scientific training to MRI users regarding data acquisition, processing and analysis. Support staff, including an experienced technical director
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elucidating the molecular and cellular mechanisms of the late phase of long-term potentiation (LTP), a key process in learning and memory. The project is based on the development and use of an innovative
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of electron microscopy and beam-material interactions. The ideal candidate will have a basic understanding of image processing. Core competencies: – Knowledge of image processing software (Avizo, Dragonfly, etc
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parameters, under direction, to ensure accurate imaging. Processes and archives images in accordance with established procedures. Inputs patient history information at time of exam/test into the practice
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service standards. By preparing and analyzing the critical metrics in the entire imaging process (exam request to final report), the individual will make data-driven suggestions to improve the delivery