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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
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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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Language Model (LLM) GPU cluster to ensure stable and reliable operation of training tasks; (b) handle GPU node failures, IB network anomalies, CUDA/NCCL errors and Kubernetes scheduling failures, perform
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junior technical staff in UMF; (c) assist in the administrative management of UMF; (d) assist in the operation of the state-of-the-art dual aberration-corrected Scanning Transmission Electron
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GPU scheduling ecosystem, including GPU Operator, container runtime, image building and pipeline engineering processes; (h) be familiar with NVIDIA Hopper GPU architecture, NCCL communication
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and servers, to ensure the smooth operation of the staff offices, studios, as well as research and computer laboratories; (b) provide technical assistance and support for teaching and learning
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in behavioural and systems neuroscience research; (d) train students and research personnel in the operation of instruments, including Electroencephalogram (EEG) system, Transcranial Magnetic
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in behavioural and systems neuroscience research; (d) train students and research personnel in the operation of instruments, including Electroencephalogram (EEG) system, Transcranial Magnetic
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and Prevention Group of HKU (stroke.hku.hk) to assist in neuroimaging data acquisition and analysis, write-up of the results, as well as training of students Apply image analysis skills on clinical and
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) assist in the implementation of strategic actions; (e) conduct essential activities for the operation in the assigned Team; (f) interact closely with stakeholders in the University; and (g