10 machine-learning-phd Fellowship positions at Hong Kong Polytechnic University in Hong Kong
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of artificial intelligence in language teaching and learning. He/She will be required to: (a) conduct independent and collaborative research on individual differences and second language acquisition; (b
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challenge issues, using advanced machine learning models and necessary techniques; (d) evaluate and validate the performance of proposed methods and algorithms through theoretical analysis; (e) maintain
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-inspired learning algorithms for efficient, robust and scalable pattern recognition; (b) assist in general management of the project; and (c) perform any other duties as assigned by the project leader
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technology for future agriculture/aquaculture; and (b) perform any other duties as assigned by the project leader, the Head of Unit or their delegates. Qualifications Applicants should have a PhD degree in
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pursuing a PhD degree. Applicants are invited to contact Prof. Rachel Yee Wai Yee at telephone number 2766 5608 or via email at rachel.yee@polyu.edu.hk for further information. Conditions of Service
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factors engineering, human-computer interaction and design; (c) user research experience and proficiency in using qualitative and quantitative research methods; (d) interest and experience in research
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experience in conducting research in ultra-precision machining field, especially in polishing or surface/subsurface characterization; and (c) demonstrated by publication in top-tier journals. Applicants
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project - “Develop an analysis tool to estimate dynamic performance of floating structures under environmental loading”. Qualifications Applicant should: (a) have a PhD degree in Ocean Engineering or
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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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twelve months] Duties The appointees will assist the project leader in the research project - “A multimodal intelligence-enabled strategy learning approach for cognitive human-robot collaborative assembly