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Description Post-Doctoral Fellow Position in Medical Image Processing (Deep Learning for Trauma CT) The Trauma Radiology AI Lab (TRAIL) in the Department of Radiology & Nuclear Medicine at the University
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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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processing and image reconstruction. Orange County is world-renowned for its natural beauty, perfect year round climate, gorgeous locales on the Pacific Ocean and incomparable recreational opportunities. Great
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University of California, Los Angeles | Los Angeles, California | United States | about 19 hours ago
Apply now to Postdoctoral Scholar in Imaging Science/Cystic Fibrosis/Rhinology Job #JPF10530 Surgery-Head & Neck / David Geffen School Of Medicin / UCLA Position overview Position title: Postdoctoral
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deep learning techniques to improve image processing and trait prediction. Analyze large datasets generated by the Phenomobile.v2+ to identify key traits affecting crop performance under stress
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Job Advertisement 2025-06 23.07.2025 At the Leibniz Institute of Atmospheric Physics (IAP), a full-time position (40h/week) in the Department “Modelling of Atmospheric Processes” is available as
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. Ophthalmology, U of S), Dr. Melody Wong (Dept. Ophthalmology, U of S), (Dr. Kerry Bishop (Optometrist, private practice) and Dr. Francisco Cayabyab (Dept. Surgery, U of S) are looking to recruit a talented and
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used in our work centre around optical imaging and spectroscopy and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics
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expertise in intravital microscopy in the Kiefer Lab at the European Institute for Molecular Imaging. Uncontrolled inflammatory processes are at the basis of many widespread diseases including myocardial
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used in our work centre around optical imaging and spectroscopy and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics