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Field
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, incorporating electronic, thermo-fluid models, and efficiency models (ii) BMS-BTMS operation policy design, which will be based on optimal control techniques and will focus on both electric power
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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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have a PhD Degree in Mechanical Engineering, Automation, Control Engineering, Mechatronics, etc. Strong background in path planning and decision-making. Candidates having relevant research or working
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control and quantum chip manufacturing. NQCT will include a large team of interdisciplinary researchers in quantum sciences and technology with ample opportunities for scientific growth and collaboration
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-qualification experience at the time of application; (b) academic background and solid knowledge of Applied Mechanics, Control Science and Engineering; (c) knowledge of control system development
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control using deep learning. Implement and test new algorithms in actual robot platforms. Job Requirements: PhD in Electrical and Electronic Engineering or related field. Hands on research experiences in
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The School of Chemistry, Chemical Engineering and Biotechnology is seeking for a full-time Research Fellow. The Research Fellow will work together with R&D team to conduct the following tasks. Key
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manufacturing scenarios. Design and develop control strategies to ensure safe robotic operations in shared and dynamic human-robot environments. Required Education Ph.D. in Electrical Engineering, Mechanical
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writing/presentation Job Requirements PhD degree in an engineering field related to this project Experience in dynamic modeling, machine learning and optimization & controls Having basic knowledge in carbon
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Power Engineering • Relevant experience in power electronics, wide band gap semiconductor devices, multilevel inverters, soft-switching high-frequency power converters, drives, control algorithms