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representation for multi-model fusion”. Qualifications Applicants for the Postdoctoral Fellow post should have a PhD degree in Computer Science, Electrical and Computer Engineering or a related discipline or an
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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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more than five years of post-qualification experience at the time of application; and (b) strong background in accounting, finance or computer science/natural language processing/machine learning
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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
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of further appointment] Duties The appointees will assist the project leader in the research project - “Multilingual speech brain-machine interface (BMI): accurately translating brain activity signal
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, machine learning systems, model merging/fusion or related areas; (b) strong self-directed learning ability; and (c) commitment to open, reproducible and ethically responsible AI research. Applicants
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, finance or computing science/natural language processing/machine learning. Preference will be given to those who are proficient in Python, adept at processing large-scale data and have worked with large
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demonstrated experience in computer vision or analysis of pathology images. The appointees will participate in a multidisciplinary collaborative research project related to development of deep learning model
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strong publication record (first-author papers in high-impact journals preferred). Demonstrated expertise in at least two of the following areas: AI/machine learning for biological modeling (e.g., virtual
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advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities such as CT, MRI, X-ray, and ultrasound. Research areas include image segmentation, detection