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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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- “Towards digital biomanufacturing – developing physics-informed machine learning framework for the advanced multi-modular 3D bioprinting system”. Qualifications Applicants should have: (a) a doctoral
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quantitative and analytical skills; (c) in-depth experience in econometric modelling and modern machine learning techniques; and (d) strong proficiency in handling large-scale datasets and advanced
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project - “The structural evolution of the Chinese aviation network during and after the pandemic: a machine learning-based approach”. He/she will be required to: (a) be responsible for the collection
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project - “Generative AI and large language models in the hotel industry: Impacts, human-machine interaction, and industry applications”. Qualifications Applicants should have: (a) an honours degree or
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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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years of post-qualification experience at the time of application; (b) experience in using machine learning for research projects; and (c) have a good command of both written and spoken English
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The appointee will assist the project leader in the research project - “MLFF-agent: autonomous discovery of machine-learning force field with large language model”. He/She will be required to: (a) be the
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. Applicant(s) should possess a Ph.D. degree, or equivalent, in biological or computer sciences or a related discipline. Experience in any of the following fields, including 1) biological image acquisition
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.) Fundamental Biology & Chemistry (molecular biology, biomaterials, tissue engineering); Artificial intelligence & Data Science related to biomedicine (machine learning, computational modeling, digital health etc