87 big-data-and-machine-learning-phd Fellowship positions at Hong Kong Polytechnic University
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AI and large language models in the hotel industry: Impacts, human-machine interaction, and industry applications”. He/She is required to: (a) assist in developing advanced machine/deep learning
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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
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-aligned research experience in federated learning, large foundation models or collaborative agents, etc.; (c) have experience in research proposal development; (d) have strong publication records in
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the research project – “Cross-correlated graph neural networks with applications in large-scale recommender systems”. Qualifications Applicants should have a doctoral degree or an equivalent qualification and
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the research projects - “Monitoring and predicting slope instability in forested terrain from multi-mode remote sensing data” and “Resilience of rural infrastructure and communities to climate change
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period: one for twelve months and one for three months] Duties The appointees will assist the project leader in the research project – “Large-scale AI-empowered reconfigurable intelligent surfaces for IOT
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materials engineering, machine learning or AI-related fields. Applicants are invited to contact Prof. Yang Xusheng at telephone number 2766 6604 or via email at xsyang@polyu.edu.hk for further information
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- “The structural evolution of the Chinese aviation network during and after the pandemic: a machine learning-based approach”. He/she will be required to: (a) conduct high-quality research in the field
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the research project - “White adipose tissue (fat) dysfunction in ageing and its related metabolic diseases: new insight and therapeutic intervention”. Qualifications Applicants should have: (a) a PhD degree
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and energy materials. Preference will be given to those with knowledge of computer programming, AI or machining learning. Applicants are invited to contact Prof. Jianguo Lin at telephone number 2766