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Field
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of myocardial fibrosis using 68Ga-FAPI-04 PET/CT (Protein Positron Emission Tomography associated with Computed Tomography using Gallium-68-labeled Fibroblast Activation Inhibitor), integrating multimodal imaging
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. The position concerns research in the above-mentioned projects. Requirements PhD degree in Medical Image Processing or a foreign degree equivalent to a PhD degree in Medical Image Processing. The degree needs
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Post-Doctoral Position - Medical Image Processing - (240000Y9) Post-Doctoral Fellow Position in Medical Image Processing (Deep Learning for Trauma CT) The Trauma Radiology AI Lab (TRAIL) in
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advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities such as CT, MRI, X-ray, and ultrasound. Research areas include image segmentation, detection
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multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities
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-driven biomarkers Initial focus will be placed on projects designed to refine and validate artificial intelligence (AI) algorithms for analyzing OCT imaging in diabetic macular edema (DME). Data processing
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, machine learning, multiscale and multiphysics simulation, computational anatomy, medical image analysis, and integration of wearables and biosignal processing, applied to conditions ranging from cardiac
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team includes a medical PhD student with pathology expertise who performs surgical specimen collection, tissue slicing, micro-CT scans, histological processing, and initial registration. The postdoc will
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3 Mar 2026 Job Information Organisation/Company IMoST - UMR INSERM 1240 Research Field Medical sciences Researcher Profile Recognised Researcher (R2) Leading Researcher (R4) First Stage Researcher
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) learning numerical methods for wave-equation-based processing, imaging, and inversion. Wave phenomena are ubiquitous in science, and they extend to objectives ranging from global Earth discovery, to natural