68 computational-physics-"https:"-"https:"-"https:"-"https:" research jobs at Hong Kong Polytechnic University
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Department of Industrial and Systems Engineering Research Assistant Professor in Smart Manufacturing Systems / Physical AI / Embodied Intelligence (three posts) (Ref. 260302010) The Department
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Department of Land Surveying and Geo-Informatics Research Assistant Professor in Smart Cities and Urban Informatics (Ref. 251208008) The Department of Land Surveying and Geo-Informatics (LSGI) is
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Department of Applied Mathematics Research Assistant Professor in Optimization and Operations Research / Statistics and Data Science / Financial Mathematics / Engineering and Computational
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Department of Applied Mathematics Research Assistant Professor in Optimization and Operations Research / Statistics and Data Science / Financial Mathematics / Engineering and Computational
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- “Towards digital biomanufacturing – developing physics-informed machine learning framework for the advanced multi-modular 3D bioprinting system”. Qualifications Applicants should have: (a) a doctoral
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for the Senior Research Fellow post should have a PhD degree in Computer Science, Artificial Intelligence, Data Science, Digital Economy or a related field plus at least six years of postdoctoral research
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project – “AI-enhanced physics for advancing reliability validation in power electronics” Qualifications Applicants should have: (a) a doctoral degree or an equivalent qualification and must have no
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Department of Computing Postdoctoral Fellow / Research Assistant (Ref. 260304011) (1) Postdoctoral Fellow (one to two posts) [Appointment period: each for twelve to twenty-four months] (2
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the research project - “Advancing generative AI algorithms for haptic rendering: bridging human-computer and human-robot interactions”. Qualifications Applicants should have a doctoral degree or an equivalent
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Department of Computing Research Assistant (Ref. 260114018) [Appointment period: six to twelve months] Duties The appointee will assist the project leader in the research project - “KCube learning