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at NTU. Key Responsibilities: The successful applicant will be responsible for Mathematical modelling for shape analysis and applications to robotics Designing, implementing, and testing algorithms
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the essentials of linear algebra, calculus, probability, statistics, algorithms, and data structures. The goal is to provide a foundational understanding of machine learning and deep learning methods
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the LLM effectiveness. Key Responsibilities: Research and develop novel ML-based methodologies and algorithms for multilingual and multimodal LLMs. Working closely with other Postdoc/RA/PhD students
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accelerated AI, machine learning, and robotics algorithms with a strong focus on computational efficiency, memory reduction, and energy-aware deployment. The role targets foundation models, including large
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— including AMRs/AGVs and exoskeletons. Proficiency in C, C++, and Python, with experience writing robust, task-specific algorithms for perception, localization, mapping, navigation, and control. Solid
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on the project of NEMO Sub-Project C: Passive UE activity inference (4/5G) from OTA network traffic. The role will focus on developing algorithms and methods for processing and analyzing 5G signals. We
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for graph data management. Design and implement machine learning models for optimizing graph data management. Conduct experiments and evaluations of the designed algorithms and systems. Help with research
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power electronics converters, control, and energy systems. Design, simulate, and implement power electronic converter prototypes and associated control algorithms. Perform experimental testing, data
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efficiency of vector search systems. The Research Engineer will work closely with the Principal Investigator and research team to design, implement, evaluate, and optimize algorithms and systems for high
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data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems, which can benefit a wide range of real-world