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advancement. The ideal candidate will have a PhD in computer science or related field utilizing computer science methods, strong expertise in medical image processing, registration and analysis and a long-term
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Education: Ph.D. or M.S. in Computer Science, AI, Computer Vision, or related field Experience: 3+ years in computer vision and deep learning, with specific focus on microscopic imaging, generation
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information into patient's charts. Assist and direct patients as needed for the following imaging modalities: General Imaging, Mammography, Computed Tomography (CT), and Ultrasound (US). Upload images from a CD
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/assisting patients and families, providing check in services for Breast Imaging and X-ray patients, scheduling BI patients for appointments, answering telephone calls and processing orders as needed
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of AI-based computer vision methods on optical and radiologic images. Our laboratory focuses on (1) intraoperative imaging with label-free optical microscopy and (2) neuro-imaging such as computed
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modalities: General Imaging, Mammography, Computed Tomography (CT), and Ultrasound (US). Upload images from a CD. Accurately record and forward phone messages. Consistently uphold the Radiology Gold Standard
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providing technical guidance to colleagues on complex issues Work with CAI colleagues and partners to develop critical processes, workflows, and training materials related for an audience of media
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recorded. Directly assists radiologist with all radiographic, angio-CT hybrid and/or ultrasound procedures. Utilizes proper archiving protocols for processing and storing all acquired images related
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and computer science. The University of Utah is building a new program in integrating radiology and pathology imaging for clinical outcomes predictions. This program provides strong mentorship for a
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anatomical and pathological diagnostic information and images as appropriate for individual disease processes. Use independent judgement to acquire the optimum diagnostic information for each examination