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, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow'. We welcome you to join our community
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optimization of multi-modal LLMs. Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content. Develop and refine machine learning and deep learning
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, Computer Science, Electronics Engineering or equivalent. Experience in one or more of the following areas: machine learning, deep learning, software-hardware co-design, computer system performance, design
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machine learning methods to the analysis of large-scale astronomical datasets, with a particular emphasis on time-domain astronomy. Research directions will be flexible and shaped according to mutual
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for machine learning and artificial intelligence, with a strong emphasis on developing and applying models such as LSTM and other time-series analyses to predict the longevity and behaviour of bioactive
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for active learning. The role will work at the intersection machine learning, high-throughput computation, and inorganic crystalline materials discovery, focusing on accelerating the design and
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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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. • The ability to work independently and collaboratively within a multidisciplinary team. • Strong writing, critical thinking, communication, and presentation skills. • Experience in Machine Learning is a
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areas. Key Responsibilities: To independently undertake research in computer vision and machine learning. To produce research reports and/or publications as required by the funding body
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testing data Development of machine learning models for battery health assessment and remaining useful life prediction Job Requirements: PhD degree in Electrical Engineering or related subjects. Expert