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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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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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computational analysis; (c) develop and validate mathematical or machine learning models; (d) prepare research reports and documentation; and (e) perform any other duties as assigned by the project
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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
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given to those with research experience in drone delivery optimization, machine learning, reinforcement learning and operation research. Applicants are invited to contact Prof. Siyuan Feng at telephone
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network and customer engagement with machine learning”. Qualifications Applicants should have: (a) an honours degree or an equivalent qualification, preferably a master’s degree or above; and (b
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VR-based tasks to study user cognition and creative performance; • process and analyse EEG data using advanced signal processing and machine learning techniques; • evaluate cognitive load
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leader in the project - “Exemplary learning, teaching and assessment practices in UGC-funded institutions in the age of GenAI”. He/She will be required to: (a) manage the logistic and administrative
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qualification; (b) strong background in extensive model optimisation on machine learning algorithm; and (c) good communication skill in English. Applicants are invited to contact Prof. Kay Chen Tan
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machine learning methods, particularly large language models (LLMs), to marketing research. Applicants are invited to contact Prof. Edward Lai at telephone number 2766 7141 or via email at edward-yh.lai