55 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at Hong Kong Polytechnic University in Hong Kong
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project - “Smart manufacturing in ultra-precision machining”. Qualifications Applicants should have a Master’s degree or a good honours degree with three or more years of research/relevant work experience
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. For the post of Research Assistant, applicants should have an honours degree or an equivalent qualification. For both posts, applicants should have relevant research experience in ultra-precision machining
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the project leader in the research project - “Project LEO (Learn-Execute-Overcome): An LLM-driven CBT journalling supporter to reduce procrastination among young adults”. He/She will be required to: (a
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English and Chinese; and (c) good teamwork spirit, self-learning ability and problem-solving skills. Preference will be given to those with experience in laboratory research, interdisciplinary projects
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) be skilled in common databases, with strong operational and maintenance abilities; (d) have excellent communication and technical learning skills, with strong problem-solving abilities and the
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abilities; (d) have excellent communication and technical learning skills, with strong problem-solving abilities and the capability to work independently; (e) be passionate about AI technology, with
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maintenance abilities; (d) have excellent communication and technical learning skills, with strong problem-solving abilities and the capability to work independently; (e) be passionate about AI technology, with
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) [Appointment period: each for twelve months] Duties The appointees will assist the project leader in the research project - “Construction skill transfer learning for smoother worker-robot collaboration in
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Learning subjects/Grade E in Other Language subjects, and the five subjects must include English Language, Chinese Language and Mathematics, with experience in Computer Science, Information Technology or a
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The appointees will assist the project leader in the project - “Advanced computational approaches for calcaneal fracture management: integrating 3D modelling, deep learning, and reinforcement learning