73 postdoc-in-automation-and-control-"Multiple" Fellowship positions at Nanyang Technological University
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involve algorithm development, simulation, test rig set-up, and experimental validation. Job Requirements: The candidate must at least have a PhD Degree in Mechanical Engineering, Automation, Control
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Engineering, Automation, Mechanical Engineering, Control Engineering, Mechatronics, Computer Science, AI, etc. Strong background in autonomous driving, deep learning, interaction modelling, prediction, robotics
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tasks using impedance control Contribute to data analysis of force/torque and kinematic data Integrate key research findings in novel robot impedance control frameworks Publish research outcome in peer
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environment. Develop robot localization approach leveraging data from multiple sensors including but not limited to camera and lidars. Develop efficient approach for multi-robot trajectory planning and tracking
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Solution Centre SAS-C, HUJ, NUS, A*STAR and industrial partners. In this job opening, we are seeking a highly motivated and visionary researcher to join our team focused on AI and data science in controlled
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sampling-based and reinforcement learning-based motion planning algorithms for multiple robotic arms in automotive manufacturing, including testing, performance evaluation in both simulation and actual
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research that covers the energy value chain from generation to innovative end-use solutions, motivated by industrialisation and deployment. ERI@N has multiple Interdisciplinary Research Programmes which
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research that covers the energy value chain from generation to innovative end-use solutions, motivated by industrialisation and deployment. ERI@N has multiple Interdisciplinary Research Programmes which
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research that covers the energy value chain from generation to innovative end-use solutions, motivated by industrialisation and deployment. ERI@N has multiple Interdisciplinary Research Programmes which
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synthesis, partitioning, and verification automation. Integrate open-source and commercial tools (e.g., SpinalHDL) to build proof-of-concept design flows Building data pipelines for learning and knowledge