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Assistant Professor of Electrical and Computer Engineering - Medical Imaging (Tenure Track) University of Oklahoma Norman Campus: Gallogly College of Engineering: School of Electrical and Computer
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"Multiscale imaging of organ-specific inflammation" (https://www.uni-muenster.de/CRC-inSight/research/area-A/A05.php ). Within this Centre, we are working together with Computer Science and Applied Mathematics
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University of Tennessee Medical Center at Knoxville | Knoxville, Tennessee | United States | about 14 hours ago
skills as required for technical support specific to image aquisition and post processing (Phillips Equipment, Xcelera, IVUS, FFR, Angiojet etc.) RTR - Radiation Certification with two years of experience
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competency and ability to support Imaging Informatics system interfaces. Req Working level knowledge of Imaging Modalities (XR, US, MRI, CT, Nuclear, Mammo, EKG). Req Strong analytical ability to find
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 9 days ago
of investigators with diverse yet complementary expertise, including imaging acquisition (MR, PET, SPECT, CT, ultrasound, and optical imaging), image analysis, imaging statistics and informatics, imaging hardware
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/video segmentation, object tracking, reinforcement learning. Deep learning Medical image computing (preferably x-ray imaging) Computationally efficient deep learning Deep learning model generalisation
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European language Excellent communication, organization, and interpersonal skills Attention to detail and accuracy Knowledge of digital image technology, photographic processes and ability to evaluate analog
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Posting Description TECHNICAL ASSOCIATE II/LAB MANAGER, Biological Engineering - Jasanoff Lab, to manage the daily operations of a neuroscience and molecular imaging research laboratory comprising
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of the following areas: Image processing, partialdifferential equations, scientific computing, deep learning.•Solid programing skills. Knowledge of Python, Tensorflow/Pytorch, and Mathematica.•Fluent
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-institutional, NIH-funded research initiative within the Computational Microscopy Imaging Lab (CMIL) focused on integrating digital pathology, spatial omics, and clinical datasets into an AI-enabled modeling