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multimodal large model-based embodied intelligence system for the elderly (AEIS-Lite)”. Qualifications Applicants should have an honours degree or an equivalent qualification. Applicants are invited to contact
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- “Building a federated learning platform for domain applications with foundation models”. Qualifications Applicants should: (a) have a doctoral degree or an equivalent qualification and must have no
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to: (a) propose a resource verification mechanism to make an untrusted device contributing sufficient computing resources to AI model training and inference as it claimed; (b) assist the project team
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- “Integration of multimodal large language model and artificial intelligence in internet marketing and consumer behaviour research”. He/She will be required to: (a) design and conduct experiments and data
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[Appointment period: six months] Duties The appointees will assist the project leader in the research project - “Causality-aware trustworthy Large Language Model”. The appointees will be required to: (a
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or developing and validating patient-reported outcome measures; (c) proficiency in statistical software such as R, Stata, SAS or Python for advanced modeling; and (d) good publication record in peer
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the research project - “Re-inventing surface haptics for robust human-machine interactions: from new modelling to psychophysical evaluation”. Qualifications Applicants should: (a) have an honours degree
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equivalent and must have no more than five years of post-qualification experience at the time of application; (b) be proficient in OceanWave3D (or equivalent) for modelling floating structures; (c) have
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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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twelve months] Duties The appointees will assist the project leader in the research project - “A vision-language model-based human guided mobile robot collaboration approach for unstructured manufacturing