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. The CT Technologist will be responsible for providing quality diagnostic imaging for medical interpretation. Duties will include operating CT equipment, handling patients, post-processing of images
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University of California San Francisco | San Francisco, California | United States | about 2 months ago
. The primary research area will focus on applying advanced multimodal brain imaging, machine learning, and signal processing methods to evaluate patients with autism and related neurodevelopmental and genetic
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complex data related to payroll, financials, and procurement, including reconciliation Processing biweekly and monthly payroll, including review and reconciliation for accuracy Updating and maintaining paid
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acquisition and processing. Image and data results are submitted for interpretation by Nuclear Medicine physicians. Exercises professional judgment in the performance of this service following the Code
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the Quantitative Imaging Platform of Villefranche (PIQv; https://sites.google.com/view/piqv ), which oversees the operation of the tools that the team develops. Those tools include imaging sensors, such as the
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Junior, Assistant, or Associate Specialist. The primary research area will focus on applying advanced multimodal brain imaging, machine learning, and signal processing methods to evaluate patients with
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roadmap for the IREC at national and international levels, • Establish processes for aligning the institute strategy for bringing research results from laboratory to the market facilitating pathways
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Sciences departments and their faculty, staff and labs. You may expect to gain experience with computer imaging, hardware, operating system and software troubleshooting, network file and printer sharing
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Researcher to join our interdisciplinary team in the Department of Electrical and Computer Engineering. This role focuses on developing and applying label-free imaging techniques, designing cutting-edge optics
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 22 days ago
resolution mammography images. The model should be trained using a combination of weakly supervised learning, for images without local annotations, and fully supervised learning, for images with corresponding