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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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the University and Boeing research agreement. They will be required to: (a) develop machine learning-based image processing algorithms for surface condition recognition, defect detection, and digital feature
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through various practical application-oriented projects, generating worldwide benefits to mankind. COMP envisions that it will become the influential icon in smart computing internationally. COMP has been
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documents, including image scanning, delivering, and filing of papers and electronic files; (d) provide administrative and logistic support to meetings and other research events; (e) maintain website
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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