31 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions at Hong Kong Polytechnic University
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project - “Enhancing older adults' healthy dining with explainable AI menu recommendations”. Qualifications Applicants should have: (a) a PhD degree in Computer Science and must have no more than five
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health monitoring, preferably with a publication record in top-tier journals; and (c) be proficient in mainstream research frameworks for deep learning and computer vision. Applicants are invited
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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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the research project – “Graphs machine learning in the era of Large Language Models (LLMs): Methods, privacy, and applications”. Qualifications Applicants for the Senior Research Fellow/Senior Project Fellow
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the project leader in the research project - “Empowering language education in the AI era: Developing students’ self-regulated learning skills in English speaking”. He/She will be required to: (a) conduct
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of the project is the application of artificial intelligence in language teaching and learning. He/She will be required to: (a) conduct independent and collaborative research on individual differences and
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machine learning methods, particularly large language models (LLMs), to marketing research. Applicants are invited to contact Prof. Edward Lai at telephone number 2766 7141 or via email at edward-yh.lai
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Department of Health Technology and Informatics Postdoctoral Fellow (Ref. 250827014) [Appointment period: twenty-four months] Duties The appointee will assist the project leader in the research
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preliminary research on the application of brain-computer interface technology in enhancing tourism experiences for families with ASD children”. Qualifications Applicants should have: (a) a doctoral degree
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and energy materials. Preference will be given to those with knowledge of computer programming, AI or machining learning. Applicants are invited to contact Prof. Jianguo Lin at telephone number 2766