55 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" Postdoctoral positions in Hong Kong
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transparency Where to apply Website https://www.timeshighereducation.com/unijobs/listing/406169/post-doctoral-fello… Requirements Additional Information Work Location(s) Number of offers available1Company
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advertisement (Ref: 532606) need not re-apply. How to Apply The University only accepts online application for the above post(s). Applicants should apply online at the University’s Careers site (https
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Post-doctoral Fellow in the Department of Orthopaedics and Traumatology, School of Clinical Medicine
continue until February 13, 2026, or until the post is filled, whichever is earlier. Where to apply Website https://www.timeshighereducation.com/unijobs/listing/405915/post-doctoral-fello… Requirements
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for the above post. Applicants should apply online at the University’s Careers site (https://jobs.hku.hk ) and upload an up-to-date C.V, quoting the job reference number, with information on current/expected
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oversee the cohort team. Enquiries about the duties of the posts should be sent to familyco@hku.hk . Information about the School can be obtained at http://sph.hku.hk . Those who have responded
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. The current publications of Prof. Zhang can be found at: https://scholar.google.com/citations?user=-mbKVoEAAAAJ&hl=en A competitive salary commensurate with qualifications and experience will be offered, in
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expected to take up a leading role to oversee the cohort team. Enquiries about the duties of the posts should be sent to familyco@hku.hk . Information about the School can be obtained at http://sph.hku.hk
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to on-campus gyms and libraries. The University only accepts online application for the above posts. Applicants should apply online at the University’s Careers site (https://jobs.hku.hk ) and upload an up
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post(s). Applicants should apply online at the University’s Careers site (https://jobs.hku.hk ) and upload an up-to-date C.V. Review of applications will start as soon as possible and continue until
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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