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in the project – “Self-paced learning platform powered by efficient graph retrieval-augmented generation”. Qualifications Applicants for the Postdoctoral Fellow posts should have a doctoral degree or
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proficiency in machine learning, statistical modeling, and data analysis using Python, R, or similar platforms. Experience in grant proposal writing, scholarly manuscript preparation, and psychological
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twelve months] Duties The appointees will assist the project leader in the research project - “Towards multimodal seamless human-robot collaboration: few-shot perception and spatial skill learning with
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challenge issues, using advanced machine learning models and necessary techniques; (d) evaluate and validate the performance of proposed methods and algorithms through theoretical analysis; (e) maintain
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with each other and other members of the Faculty. Fellows will be expected to teach two courses during the term of their appointment and are required to submit a brief annual summary of their activities
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and energy materials. Preference will be given to those with knowledge of computer programming, AI and/or machining learning. Applicants are invited to contact Prof. Jianguo Lin at telephone number 2766
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-inspired learning algorithms for efficient, robust and scalable pattern recognition; (b) assist in general management of the project; and (c) perform any other duties as assigned by the project leader
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Applied Learning subjects / Grade E in Other Language subjects, and the five subjects must include English Language, Chinese Language and Mathematics. Applicants are invited to contact Prof. Tam Hwa-yaw
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pure mathematics. The possibility of renewal for a third year is subject to satisfactory performance and mutual agreement. The successful candidate will only be required to teach one course during the
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research areas, preferably demonstrated by publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential