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- “From waste tires to value-added products: novel valorization process design, simulation, optimization and analysis”. Qualifications Applicants should: (a) have a doctoral degree or an equivalent
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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
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qualification; (b) have experience in conducting research, and skills in process systems engineering and AI for modelling industrial systems; and (c) be proficient in English. Applicants are invited
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: (a) a PhD degree in Applied Linguistics, Second Language Acquisition, Psycholinguistics or a related discipline, or an equivalent qualification and must have no more than five years of post
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Assistant, applicants should have an honours degree or an equivalent qualification. For all posts, applicants should have a strong background in materials processing technologies, especially for light alloys
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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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project - “Development of an intelligent process system for ring forging manufacturing based on AI deep machine learning”. Qualifications Applicants should have a doctoral degree plus substantial
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computer software; (b) good interpersonal and communication skills; (c) excellent communication and interpersonal skills in working with people at different levels in a university setting; and (d
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- “Establishment of the PolyU-DRRC novel material science and technology innovation centre”. He/She will be required to: (a) prepare and process textile data for AI training; and (b) perform any other duties
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behavioural and EEG experiments; (d) assist in recruiting and running participants for behavioural and EEG studies; (e) assist in processing and analysing behavioural and EEG data; and (f) perform any