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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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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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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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: Preferably PhD degree in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Independent, highly analytical, proactive and a team player Excellent teamwork and verbal, written
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other duties relevant to the programme of research. Job Requirements: PhD degree or at least 8 years working experience in Computer Engineering, Computer Science, Electronics Engineering or equivalent
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neuroimaging experiments, proficient in image processing and programming paradigms. The successful candidate will contribute to ongoing multidisciplinary research and play an active role in developing novel
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, electrical & electronic engineering, or equivalent. Background knowledge in signal representation/processing, visual data compression, and data-driven and machine learning/analysis. Prior research experience
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University of Singapore is a multi-disciplinary institute committed to developing new paradigms for biomedical research by focusing on the quantitative analysis of dynamic functional processes. Through
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) The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena