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the curriculum is Climate Practice—connecting academic theory with hands-on experiential learning, corporate decarbonization projects, and field-based risk assessment. Duties and Responsibilities
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The appointees will work on a cross-institutional project dedicated to supporting primary students in Hong Kong to learn Chinese, and to enhance their use of Chinese as a medium of learning. Working closely with
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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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Post-doctoral Fellow/Senior Research Assistant in the Centre for Information Technology in Education
. Applicants should possess a doctoral or master’s degree in Education, the Learning Sciences or a related discipline, with a strong background in technology-enhanced learning and assessment, learning design and
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motivated, creative with excellent communication skills in written and spoken English and Cantonese. Expertise and knowledge in bioinformatics, deep learning and/or biomedical image and clinical data analysis
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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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combination of results in five HKDSE subjects of Level 2 in New Senior Secondary subjects / "Attained" in Applied Learning subjects / Grade E in Other Language subjects, and the five subjects must include
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-institutional project dedicated to supporting primary students in Hong Kong to learn Chinese, and to enhance their use of Chinese as a medium of learning. Reporting to the Project Leader, he/she will assist
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learning and LLM libraries; and (d) have experience with data collection and processing in medical/health-related tasks in Chinese/Cantonese is a plus. Applicants are invited to contact Prof. Chersoni
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of environmental factors of 60,000 subjects across multiple time points. Our research laboratory has great computing capacity, including multiple H100 and A100 GPU systems for deep learning, and computing clusters