411 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" uni jobs at Nanyang Technological University
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vision by designing, developing, and optimizing robust distributed learning frameworks and deep learning models for visual recognition and person re-identification. Key Responsibilities: Design and conduct
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Master’s degree in Electronic Engineering, Computer Science, or related field Knowledge of pinching antennas, wireless communications, and machine learning Strong analytical, research, and scientific writing
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Requirements Master’s degree in Electronic Engineering, Computer Science, or related field Knowledge of pinching antennas, wireless communications, and machine learning Strong analytical, research, and
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innovation. The Platforms Engineering Group builds and operates the infrastructure and systems that enable AI practitioners across AISG's programmes to develop, train, and deploy machine learning models
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Science of Learning research team in developing brain-based machine-learning predictive models for early identification of mathematical learning difficulties in kindergarten and early primary level students
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implementation of data-driven computer vision and machine learning models using sensor data, camera feedback, and process parameters for print and tool path planning and process optimisation. Deploy real-time
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developers, and AI researchers to translate findings into operational use cases. Prepare data collection frameworks and work on fish health monitoring datasets for machine learning training and benchmarking
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innovation. The Platforms Engineering Group builds and operates the infrastructure and systems that enable AI practitioners across AISG's programmes to develop, train, and deploy machine learning models
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data analysis through to deployment and documentation. Applied Machine Learning: Possess deep, practical knowledge of machine learning fundamentals, with proven experience applying algorithms to solve
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, machine learning, and deep learning models. Key Responsibilities: Develop and apply time-series forecasting methods for semiconductor equipment health monitoring. Analyze equipment degradation data