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orientation and multi-tasking abilities Microsoft Excel (able to write excel formulae with respect to marks algorithm) Working around 20 weekends in a year and occasionally after office hours are to be expected
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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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multimodal AI algorithms for fire, smoke, and hot-work detection by fusing optical, thermal/infrared, LiDAR, RADAR, and gas sensor data under varying environmental conditions. Design computer vision and human
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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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implement optimization models tailored to transportation and logistics contexts. Develop and refine custom heuristics and metaheuristics (e.g., Tabu Search, Genetic Algorithms) to solve large-scale, real
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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