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analysis; (b) develop and evaluate AI and machine learning models; (c) manage data collection and research activities; (d) prepare reports, publications, and project documentation; and (e) assist in project
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machine learning-enhanced algorithm incorporating domain knowledge for sustainable maritime transport”. Qualifications Applicants should have: (a) an honours degree, preferably in mathematics, logistics
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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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School of Design Research Assistant (Ref. 251024008) [Appointment period: six months] Duties The appointee will assist the project leader in the research project - “AI-powered creative learning
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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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project - “Deep learning-based approach for process parameter optimization of SiC wafer under limited data”. He/She will carry out research in the areas of machine learning and data science, and also be
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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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measurements of indoor environmental quality (IEQ), energy simulations, and machine learning modelling; (b) strong analytical and problem-solving skills, with the ability to conduct research independently
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health monitoring, preferably with a publication record in top-tier journals; and (c) be proficient in mainstream research frameworks for deep learning and computer vision. Applicants are invited