241 postdoctoral-image-processing-in-computer-science-"U" Fellowship positions at Nanyang Technological University
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The School of Chemistry, Chemical Engineering and Biotechnology (CCEB) invites applications for the position of Research fellow. The Research Fellow will take on a significant role in research
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record. Proficient oral presentation, report writing and multitasking skills. Competent in using membrane technology and separation technologies. Relevant research experience on electrochemical processes
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involving speech/audio, images, and video along with text-based applications. Job Requirements: MSc (Research Associate) or PhD (Research Fellow) in Electrical Engineering, Computer Science, Statistics
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necessary lead relevant meetings. To undertake any other duties relevant to the programme of research. Job Requirements: PhD degree in Computer Engineering, Computer Science, Electronics Engineering or
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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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Join Our Team at the School of Biological Sciences, Nanyang Technological University, Singapore The School of Biological Sciences (SBS), part of the College of Science, was established in 2002 with
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The School of Chemistry, Chemical Engineering and Biotechnology (CCEB) invites applications for the position of Research Fellow. We are looking for skilled chemist to design and preparation
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products. Apply the knowledge to correlate results / system operation. Set-up and monitor the performance of systems Job Requirements: PhD degree in a relevant Science or Engineering field Strong analytical
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The School of Materials Science and Engineering (MSE) provides a vibrant and nurturing environment for staff and students to carry out inter-disciplinary research in key areas such as Computational
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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