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theoretical analysis, including stability estimates and convergence proofs, to guarantee the reliability of the developed algorithms. Design and execute high-fidelity numerical simulations for PDE-based models
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from chip. Characterise and optimise the algorithm for signal data processing for real-time cell analysis. Develop a user-interface platform for end-user testing of clinical samples. Job Requirements
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accelerator design, verification, and physical implementation using open-source tools. Explore architecture-algorithm co-design for machine learning and AI acceleration. Perform performance, power, and area
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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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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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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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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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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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. 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