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by ARPES, pursue scalable wafer-scale moiré epitaxy, develop epitaxial superconductors for quantum computing and integrate machine learning for automated high-throughput MBE. We are particularly
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, Effects, and Criticality Analysis (FMECA), functional FMECA, advanced sensing techniques, sensor and operational data fusion, data analytics, and machine learning algorithms for condition monitoring, fault
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solving complex problems at the intersection of wireless communications, edge computing, and machine learning, and who is eager to translate theoretical insights into practical, IoT systems. Key
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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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is to develop real-time truck-drone collaboration system to enhance Singapore safety and resilience and using learning-based approaches. Key responsibilities include: Collecting and analyzing relevant
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Responsibilities: To perform pioneer research in scent digitalization and computation. To further develop machine learning tasks for scent signal classification/fusion. Set up and analyze experiments under different
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Develop instrumentation and fixtures for the automation. Capabilities in advanced finite element or machine learning tools for process optimisation Disseminate the research outcomes into Journal
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., • Interest in developing risk prediction models via deep learning/machine learning. • Have strong background in DL, EEG data and programming for the implementation of proposed methods. Apply now
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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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, 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