15 humanities-"https:"-"https:"-"https:"-"https:"-"https:" positions at Hong Kong Polytechnic University
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, artificial intelligence, software engineering, human-computer interaction (HCI), data science, or a related discipline], or other relevant interdisciplinary disciplines (e.g. biomedical engineering, healthcare
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– “A human-like progressive learning paradigm for embodied AI: Meta skills for robots by watching and imagination”. They will be required to: (a) identify irreducible low-level sensorimotor units
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project - “Utilising education spaces as test-beds: Harnessing human-environment interaction data to achieve thermal comforts and energy saving in University classroom”. Qualifications Applicants should: (a
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twelve months] Duties The appointees will assist the project leader in the research project - “A memory-enhanced AI agent coordination system for human-centric manufacturing process monitoring and
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in research projects of human motion, foot geometry, collection and analysis of ergonomic, kinematic and kinetic data; and (c) a good command of English. Preference will be given to those with
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Division of Artificial Intelligence and the Humanities Research Assistant (two posts) (Ref. 260810009) [Appointment period: each for six to twelve months] Duties The appointees will assist
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the research project - “Development of human-centric driver support systems and training recommendations for safer cross-border driving during northbound travel for Hong Kong vehicles”. Qualifications Applicants
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- “Closed-loop human-AI integration for cognitive and physical augmentation”. The appointees will be required to: (a) perform research about using generative AI to discover new patterns to support mobile
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twelve months] Duties The appointees will assist the project leader in the research project - “Mutual cognitive human-robot collaborative manufacturing systems 1”. Qualifications For the post of
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twelve months] Duties The appointees will assist the project leader in the research project - “A vision-based human digital twin modelling and scene understanding approach for adaptive and natural task