213 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" research jobs in Hong Kong
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proficiency in machine learning, statistical modeling, and data analysis using Python, R, or similar platforms. Experience in grant proposal writing, scholarly manuscript preparation, and psychological
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Department is available on the departmental website at www.polyu.edu.hk/hti/ . We are looking for a highly motivated personnel with expertise in bioinformatics, neuroimaging, machine learning, mental health
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to formulate mathematical models of the problems and develop efficient solution methods, particularly by leveraging techniques from machine learning and operations research. b) The applicants are expected
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of Artificial Intelligence (AI) into higher education. The appointee will play a key role in advancing PolyU’s strategic initiatives in digital transformation, teaching innovation and AI-enabled learning. Key
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Science, or an equivalent qualification; (b) experience in field measurements of food waste, bioconversion and machine learning modelling; (c) strong analytical and problem-solving skills, with
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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 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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Psychology, Cognitive Neuroscience or other related disciplines; (b) be proficient in computer programming, e.g. Matlab and R; (c) have a good command of both written and spoken English; and (d) have
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’ post-qualification experience, preferably in the field of education. They should also have a good command of written and spoken Chinese, and experience in IT applications and Chinese computer operations
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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