289 cloud-computing-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"BioData" positions in Hong Kong
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interpersonal skills; (d) have a good command of both written and spoken English and Chinese, with fluency in Putonghua; and (e) have proficient computer literacy. Shortlisted candidates will be invited
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a minimum of three years’ relevant work experience; (b) a good command of both written and spoken English and Chinese, with fluency in Putonghua; (c) good computer literacy; (d) good
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teamwork, interpersonal and communications skills; (c) good problem-solving skill with the ability to work independently and proactively; (d) proficiency in computer applications and IT skills; and (e) a
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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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by the Dean of Faculty and/or Head of Department or their delegates. Qualifications Applicants should have: (a) a recognised degree, preferably in Multimedia Design, Design, Computer Science or a
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and interpersonal skills; (c) a good command of both written and spoken English and Chinese; (d) ability in organising and coordinating functions and events; and (e) good computer literacy and
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-qualification working experience; (c) good computer literacy; (d) a good command of both written and spoken English and Chinese, preferably with fluency in Putonghua; (e) the ability to work
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interpersonal and communication skills; (d) a good command of English and Chinese, with fluency in Putonghua being an advantage; (e) high self-motivation; and (f) good computer literacy. Shortlisted
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Department of Computing Research Assistant Professor in AI and Digital Transformation for Education (three posts) (Ref. 260226006) The Institute for Higher Education Research and Development (IHERD
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Department of Computing Research Assistant (Ref. 260114018) [Appointment period: six to twelve months] Duties The appointee will assist the project leader in the research project - “KCube learning