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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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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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/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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(formerly the Australian Technology Park). Your key responsibilities will be to: Undertake original research in developing methods of cone beam computed tomography interventional imaging undertake
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/Qualifications Who you are You have a Professional Master’s degree or PhD in electrical/software engineering or equivalent through experience. You have 3-5 years of experience in computer vision and image
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Laboratoire de Physique des Interfaces et des Couches Minces (LPICM), UMR CNRS/École Polytechnique, | Palaiseau, le de France | France | about 7 hours ago
multidisciplinary team involving image processing labs (e.g., CMAP) and French hospitals (e.g., CHU Kremlin-Bicêtre, Hôpital Foch, Institut Mutualiste Montsouris, Institut Gustave Roussy). Phase 1: Design and develop
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scientists dedicated to advancing medical imaging research. The primary focus of our group’s endeavors is quantitative image analysis and artificial intelligence (AI), with a specific emphasis on pioneering AI
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other small animal models with multimodal imaging. The modalities available include 2D and 3D optical bioluminescence, fluorescence, radio/chemi luminescence, X-ray micro-computed tomography, and nuclear
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Treatment. The post-holder will work in the School of Biomedical Engineering & Imaging Sciences, King’s College London, with a team of investigators covering AI, computer vision, robotics, and medical imaging
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School of Biomedical Engineering & Imaging Sciences, King’s College London, with a team of investigators covering AI, computer vision, robotics, and medical imaging. You will join a dynamic and successful