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strategy. Application Procedure The University only accepts and considers applications submitted online for the post above via the CUHK career site. For more information and to apply online, please visit
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Professor (Ref: 250000QB) (Closing Date: August 1, 2025) The Faculty of Engineering of The Chinese University of Hong Kong (CUHK) is now seeking an outstanding candidate in the area of the AI Computer Systems
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for PhD positions. As a member of our team, you will have the opportunity to collaborate on cutting-edge technologies like quantum simulators, Bose-Einstein Condensates, and quantum information processing
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sustainability issues - Materials Science: AI-driven discovery and design of new materials Applicants should have (i) a Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or a closely related
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operation of embodied agents. - Multi-Agent Systems: Building collaborative robotic systems that can communicate, coordinate, and achieve shared goals. - Robot Learning and Reinforcement Learning: Advancing
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Process: Applications must be submitted online through the CUHK-Shenzhen PhD Application Portal . The university recommends that applicants contact their intended supervisor before applying, which should be
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Scholars' Forum, which will be held from August 22 to 23, 2025, online via Zoom. This Forum is a crucial part of our faculty recruitment process. We are delighted to announce and invite outstanding young
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postdoctoral fellows, who will be interested in one of the following topics: 1) Theoretical condensed-matter physics 2) Quantum information processing 3) Strong light-matter interactions Requirements: PhD in
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experiment. The group is particularly interested in the detection of solar neutrinos, solar axions, and light dark matter. About the Position: The successful candidate will play a key role in the operation and
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/finance and https://grad.bschool.cuhk.edu.hk/wp-content/uploads/FIN-Top-Publications.pdf respectively. Application Procedure The University only accepts and considers applications submitted online