46 machine-learning "https:" "https:" "https:" "https:" "https:" positions at Nanyang Technological University in Singapore
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middleware (e.g., ROS, MoveIt) and hardware integration. Knowledge of machine learning, reinforcement learning, or vision-language models for robotics is a plus. Hands-on experience with robotic arms (e.g
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Responsibilities: Electrochemical process on interface phenomena Battery testing under different conditions Simulation of scaled up process. Interface with machine learning group on data base set up Battery safety
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in the 2025 QS World University Rankings by Subjects. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Research Fellow to advance cutting-edge research in the security
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of servers and assistance in network setup in a testbed building. Data collection from BMS and thermal and occupancy sensors, and machine learning based analysis. Daily system maintenance for the servers and
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analytics and machine learning techniques. Familiar with software implementation. Good written and oral communication skills. Interpersonal skill (e.g. Ability to work independently / develop solutions under
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. Publication of research papers and IPs. To assist project PI to coach research students. Job Requirements: A Bachelor’s degree in relevant fields with past experience in embedded system, machine learning and
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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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machine learning and AI acceleration. Perform performance, power, and area (PPA) analysis of processor and accelerator designs. Publish research findings in top-tier conferences and journals and contribute
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of wireless communications, signal processing and machine learning methods and algorithms for urban anomaly detection and human activity classification through 5G signal recording, processing analysis
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workflows for processor and accelerator design, verification, and physical implementation using open-source tools. Explore architecture-algorithm co-design for machine learning and AI acceleration. Perform