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at NTU. Key Responsibilities: The successful applicant will be responsible for Geometric modelling for shape analysis and robotics Designing, implementing, and testing algorithms Engaging in scientific
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segmentation algorithms to segment industrial wrapped objects with limited data Develop algorithms to identify the most reliable segmented objects. Develop algorithms to determine the best grasp pose based
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, implementing, and testing algorithms Engaging in scientific exchange with collaboration partners of the project Preparing reports, scientific papers, and presentations Job Requirements: Master’s degree in
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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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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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— 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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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