43 image-coding-"University-of-Manchester" Fellowship positions at Nanyang Technological University
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an emphasis on technology, data science and the humanities. We are looking for a Research Fellow to conduct AI for medicine research. The role will focus on developing foundation models to medical image
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of imaging this highly dynamic and complex organelle. Our lab has developed various quantitative and super-resolution imaging tools specifically designed for studying the Golgi, including en face averaging
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in a meritocratic culture. Key Responsibilities: Design and build optical interferometric imaging setup for imaging live cells Conduct in-vitro imaging experiments Analyze and summarize
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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 a mission to advance biological and biomedical sciences. At SBS, our research spans various...
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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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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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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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. The roles of this position include: Development of algorithms to improve memory/sample/time efficiency of LLM training. Development of a workable prototype system with capabilities such as conversational