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, preference will be given to those with strong Python/programming and research skills, and experience in graphs/ontologies, machine learning, optimisation/control, time-series forecasting, BMS/HVAC, PV or ESS
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-science and signal-analysis tasks, including processing experimental signals, integrating datasets, developing machine-learning models, and mapping measured fuel properties to SAF performance. For the post
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., LangChain, AutoGen, Unity ML-Agents); and (e) experience in integrating AI/machine learning models with web applications or game engines. Applicants are invited to contact Dr Zackary P. T. Sin at telephone
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- “Reliable industrial foundation models for trustworthy industrial robot fault diagnosis in automotive smart manufacturing”. He/She will be required to: (a) carry out research in advanced machine learning
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- “Smart Holistic Insurance Enhancement using Learning Algorithms & Decentralization (S.H.I.E.L.D.)”. He/She will be required to: (a) develop machine learning models to predict optimal rehabilitation
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related field; (b) hands-on experience with programming (e.g., Python); (c) an interest in AI, machine learning, signal processing, or human-computer interaction; and (d) a passion for creating
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- “Experimental investigation into the mechanisms of plasma-assisted combustion for green liquid propellants”. Qualifications Applicants should have: (a) a doctoral degree, preferably in machine learning‑driven
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have: (a) an honours degree in Biomechanical Engineering, Apparel and Textile Design Technology, Machine Learning, Data Science or related disciplines or an equivalent qualification; and (b) good
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should: (a) have a good honours degree or an equivalent qualification; (b) have a good command of both written and spoken English and Chinese; (c) be proficient in Python and with the main machine
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Computer Science, Artificial Intelligence, Data Science Engineering or a related discipline; (b) demonstrated expertise in foundation models, generative AI, multimodal learning, machine learning systems, model