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health assessment through visual behavior recognition, image-/video-based analytics, and biosignal interpretation (e.g., growth rate estimation, movement, coloration). Design and implement experiments
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Ultrasound (UDUS) Research Group and the Michigan Institute for Imaging Technology and Translation (MIITT) at the University of Michigan. Our team is positioned at the interface of ultrasound (US) and magnetic
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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strategies, SiP and chiplet architecture Fault tolerance, robustness and reliability Functional / Cryptographic agility in hardware Prototype and design new architectural innovations, including chiplet
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chiplet architecture Fault tolerance, robustness and reliability Functional / Cryptographic agility in hardware Prototype and design new architectural innovations, including chiplet oriented architectures
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interested in candidates with experience in metaoptics, biosensing, and structured light. The ideal start date for the position is September 1, 2025 (negotiable). The Leung Research Group’s vision is to
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requirements: PhD degree in Computer Science, Electrical and Electronic Engineering, or related field. At least 3 years of relevant experience in computer vision, artificial intelligence, etc. Proficiency in
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. The position is for one year, renewable subject to satisfactory performance. Successful candidates will conduct research and develop 3D vision. Candidates are expected to have a strong background in relevant