83 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL" positions in Hong Kong
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. More information about the Faculty can be found at https://web.edu.hku.hk/ . The Position We now invite applications for appointment as Professor/Associate Professor/Assistant Professor in Learning
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. More information about the Faculty can be found at https://web.edu.hku.hk/ . The Positions We now invite applications for appointment as Professor/Associate Professor/Assistant Professor in Learning
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as a research-led comprehensive university through upholding the highest international standards of excellence in its research pursuits, scholarship, teaching and learning, and service to the community
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Ref.: 533588 Work type: Full-time Department: Teaching and Learning Innovation Centre (47500) Categories: Senior Research Staff & Post-doctoral Fellow, Research Staff Post-doctoral Fellow/Senior
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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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) have strong knowledge of and background in electromagnetic device design, power electronics and machine learning; (c) have hands-on experience in electrical and electronic engineering; (d) have
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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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- “Deep learning-based approach for process parameter optimization of SiC wafer under limited data”. He/She will carry out research in the area of machine learning (ML) and data science, and also be
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qualification; (b) experience in using machine learning for research projects; and (c) have a good command of both written and spoken English. Applicants are invited to contact Prof. Yoo Hee Hwang
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and energy materials. Preference will be given to those with knowledge of computer programming, AI and/or machining learning. Applicants are invited to contact Prof. Jianguo Lin at telephone number 2766