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UnitedKingdomTime) Position Description: Apply Position Description We invite talented and motivated applicants for PhD and Postdoc positions in the group of Haowei Xu (https://www.haoweixu.com/ ) at the Department
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slide imaging analysis in computational pathology is essential. Applicants should have a solid publication record and demonstrated experience in computer vision or analysis of pathology images
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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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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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to better understand, diagnose and treat diseases with particular interests in cancer and neurodegenerative diseases. We are a highly collaborative and multidisciplinary lab eager to create an impact on
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neuroscience (23240033) Understanding how adaptive and maladaptive behavior emerges from the operation of neuronal circuits is a central topic across different sub-disciplines within neuroscience. Our
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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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, Computer Science, or other related disciplines, with experience or keen interest in processing magnetic resonance imaging (MRI), such as arterial spin labeling and diffusion tractography using programming scripts
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motivated, creative with excellent communication skills in written and spoken English and Cantonese. Expertise and knowledge in bioinformatics, deep learning and/or biomedical image and clinical data analysis