46 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at Hong Kong Polytechnic University
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and develop novel extended reality paradigms/algorithms for computer-assisted surgery; (c) research and develop novel learning algorithms via effective fusion of empirical knowledge, human
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for computer-assisted surgery; (c) research and develop novel learning algorithms via effective fusion of empirical knowledge, human interactions and machine inference; (d) write papers, reports and
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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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experience at the time of application. Preference will be given to those with: (a) a PhD degree in GIScience, Geomatics, Computer Science, Big Data, Machine/Deep Learning, Artificial Intelligence or a
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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
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) have a good knowledge of computer vision and programming skills; and (c) be willing to learn research methods, data processing and data analysis. Applicants are invited to contact Prof. Lawrence W. C