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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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that are relevant to industry demands while working on research projects in SIT. The primary responsibility of this role is to support and contribute to an industry innovation research project. The Research Engineer
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-world conditions to verify system operation against targets and demonstrate the reliability of the technology for use in backup power, grid stabilisation, and renewable energy integration applications
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disease patients using radiation therapy. The primary aim of this research is to develop real-time target tracking and/or dynamic imaging algorithms for implementation within radiotherapy and medical
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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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internationally recognised for its research in craniofacial biomechanics. Located in UCL Mechanical Engineering and supported by state-of-the-art imaging and material characterisation facilities, the lab focuses
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Universities; and #8 for Data Science and AI by QS World University Ranking. A hot bed of cutting-edge technology and groundbreaking research, the College aims to groom the next generation of leaders, thinkers
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under real-world conditions to verify system operation against targets and demonstrate the reliability of the technology for use in backup power, grid stabilisation, and renewable energy integration