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in Law and Sustainable Development in the Faculty of Law (Ref.: 534377), to commence on July 1, 2027, or as soon as possible thereafter, on a three-year fixed-term basis, with the possibility
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for diagnosis and prognosis of different sarcomas. He/she will develop and train deep learning models with state-of-the-art algorithms based on histology whole slide images. They may also contribute to research
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. The successful candidate will be able to teach one of the undergraduate courses related to AI/ML, programming languages, data structures and algorithms, operating systems, network security, visualization, and
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multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities
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integration; (b) conduct algorithm research and development in areas such as computer vision, multimodal learning and embodied AI; (c) conduct experiments, data collection and performance evaluation; (d
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to machine learning, data analysis, and software development; Assisting in the design of experiments, algorithm coding, and analysis of large datasets; Developing and maintaining websites and web applications
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) experience in large model training, knowledge distillation or efficient deep learning algorithm development, foundation model implementation and optimisation; and (c) good communication skills in English
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human-centred collaborative robotic systems, with emphasis on embodied intelligence and shared autonomy; (c) develop algorithms for human intention understanding, multimodal perception and fusion and
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. The successful candidate will be able to teach one of the undergraduate courses related to AI/ML, programming languages, data structures and algorithms, operating systems, network security, visualization, and
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self-driven, highly motivated, creative with excellent communication skills in written and spoken English and Cantonese. Expertise and knowledge in AI deep learning model development on histology whole