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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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Matter Physics / cond-mat-th , Condensed Matter Physics, Electronic Structure, Strongly Correlated Materials , Condensed Matter Theory , Strongly Correlated Materials , Superfluidity and superconductivity
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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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Ph.D. degree in Epidemiology, Biomedical Sciences, Computer Science, Data Science, or related disciplines. A proven track record in peer-reviewed publications and research experience in computer graphics
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-of-the-art techniques to assess the physicochemical properties of nanoparticles, ensuring their stability, drug release kinetics, encapsulation efficiency and electron microscopy imaging. Integrate innovative
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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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. Qilei CHEN at chenql@hkbu.edu.hk . The subject of the email should be: Application-Personal Name-Position Applicable. The initial appointment will be offered on a fixed-term contract of up to 1 year. Re
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Artificial Intelligence (DSAI) is a multi-disciplinary department hosted under the Faculty of Computer and Mathematical Sciences established on 1 January 2025. DSAI will be at the forefront of cutting-edge
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Avenue, Kowloon Tong, Hong Kong [Email : hrojob@cityu.edu.hk/Fax : 2788 1154 or 3442 0311]. To apply, please submit an online application at https://jobs.cityu.edu.hk. ; Applications will receive full