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for drone swarms. The role will focus on multi-agent visual perception techniques. Group website: https://personal.ntu.edu.sg/wptay/ Key Responsibilities: Develop signal processing and machine learning
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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context. • Conduct statistical analyses, longitudinal modelling, or machine learning approaches as appropriate. • Develop documentation, codebooks, or tools to support reproducible research. • Lead
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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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). Applying advanced statistical and machine learning methods (e.g., predictive modelling, clustering, multivariate integration) to large-scale time series and sensor datasets. Contributing to the development
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research in Physics-Informed Machine Learning (PIML) for metal additive manufacturing process. This role will focus on developing novel machine learning frameworks that seamlessly integrate physical
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital
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for drone swarms. The role will focus on multi-agent visual perception techniques. Group website: https://personal.ntu.edu.sg/wptay/ Key Responsibilities: Develop signal processing and machine learning