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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
. The students will work closely with experts on healthcare data, AI/machine learning, computer vision, and big data processing Duration: The research fellowship(s) will have the duration of 3 months. It’s
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POSITION HIGHLIGHTS • The Radiology Technical Assistant provides general support to the Imaging Department. This includes preparing the patient for the procedure/ exam, transporting the patient, assisting
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wide range of academic fields, Ghent University is a logical choice for its staff and students. Image Processing and Interpretation (IPI, http://ipi.ugent.be ) is an imec research group at Ghent
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Procedure Applications must be exclusively submitted on the admissions platform of the Instituto Superior Técnico at https://fenix.tecnico.ulisboa.pt/fenixedu-admissions and requires registration and
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Apple Device Enrollment Program and Mobile Device Management (MDM) capabilities of Jamf Pro to simplify enrollment and setup processes. Review device configuration to ensure success and identify trouble
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for collaborative research within the University and with community partners, including active programs in artificial intelligence, quantitative imaging, and imaging informatics with direct clinical translation
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exams in accordance with departmental procedures, selects proper technical factors, reviews and evaluates Ultrasound images to determine that they are satisfactory for diagnostic purposes and assesses
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transparency throughout the recruiting process. Excellent benefits are available; for details, see http://benefits.umich.edu/ Union Affiliation This position is included in the bargaining unit represented by
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initiatives, including evaluating program effectiveness and continuously improving offerings based on emerging technologies and user feedback Strong knowledge of AI concepts, prompt engineering, and experience
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Area: Computer Vision Group: Pattern and Image Analysis Work Objectives: In terms of deep learning architectures for object detection, particular attention will be given to the analysis of performance