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advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities such as CT, MRI, X-ray, and ultrasound. Research areas include image segmentation, detection
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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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’ 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
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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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) 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