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models, focusing on industrial image analysis Develop advanced deep learning methods for power battery inspection models Design and implement novel algorithms for AI-based CT imaging Lead experimentation
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learning, Large Language Models, Stochastic optimization, Transfer & Evolutionary optimization, Bayesian optimization for complex design in material and engineering. Key Responsibilities: Collect relevant
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with industrial communication protocols (e.g., CAN, Modbus); and experience with embedded C/C++ programming for implementing control algorithms on DSPs and FPGAs. Ability to lead a team and work
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focused on using advanced numerical methods to explore low energy dynamics in strongly interacting quantum spin systems. The candidate will develop and implement advanced algorithms to investigate
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communication skills. Proficiency in developing deep learning models using frameworks such as PyTorch and TensorFlow. Research experience in medical image analysis using deep learning algorithms. Strong track record in
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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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industry and international partners. For more details, please view https://www.ntu.edu.sg/atmri . We are looking for a Research Fellow to conduct research on air traffic management (ATM) algorithms and data
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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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. The Research Fellow will be employed and based at NTU, and is expected to travel overseas to collaborate with scientific teams at CEA, France. The holder will: Apply advanced machine learning algorithms
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propulsion, onboard microgrids, EMS algorithms, and real-time validation platforms. Project & Research Responsibilities: Participate in and support the execution of the research project with the Principal