21 parallel-processing-"EURAXESS" Postdoctoral positions at THE UNIVERSITY OF HONG KONG in Hong Kong
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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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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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concentrate on three interrelated areas: a) Semiconductor Equipment Scheduling: In semiconductor fabs, a vast number of wafers are processed across hundreds or even thousands of manufacturing tools following
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Manage, process, and analyse complex real-world healthcare datasets to generate insights and evidence. Develop and implement data pipelines for the ingestion, curation, and transformation of RWD
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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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are in the process of completing a Ph.D. degree will also be considered. The appointee will work with Prof. Zi Yang Meng to conduct research on computational and theoretical condensed matter physics. Areas
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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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Data Scientist. We now invite applications for the captioned post. Duties and Responsibilities Manage, process, and analyse complex real-world healthcare datasets to generate insights and evidence
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analytical field-theoretical approaches is desirable. Applicants who are in the process of completing a Ph.D. degree will also be considered. The appointee will work with Prof. Zi Yang Meng to conduct research
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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