58 evolution "https:" "https:" "https:" "CMU Portugal Program FCT" Postdoctoral research jobs in Hong Kong
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at https://hro.hkbu.edu.hk/en/worklife-at-hkbu/employee-favourable-environment.html#privacy-policy . The University reserves the right not to make an appointment for the post advertised, and the appointment
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of the University's Personal Information Collection Statement can be found at https://hro.hkbu.edu.hk/en/worklife-at-hkbu/employee-favourable-environment.html#privacy-policy . The University reserves the right not
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information, please contact Professor Stephanie Ma at stefma@hku.hk . Details of Professor Ma’s research can also be found at http://thesmalab.com/ . Information about the School of Biomedical Sciences can be
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@hku.hk . Details of Professor Ma’s research can also be found at http://thesmalab.com/ . Information about the School of Biomedical Sciences can be obtained at http://www.sbms.hku.hk/ . A highly
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philosophy, social philosophy, aesthetics, and other cognate areas). This appointment will be affiliated with the Hong Kong Ethics Lab: https://www.hkethicslab.com . The post-doctoral fellow is expected
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professional development. The University only accepts online applications 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
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) We now invite applications for the captioned post. Duties and Responsibilities Assist in a collaborative research project on the development and widespread implementation of a telerehabilitation
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their applications unsuccessful. Details of the University’s Personal Information Collection Statement can be found at https://hro.hkbu.edu.hk/en/worklife-at-hkbu/employee-favourable-environment.html#privacy-policy
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The University only accepts online applications for the above posts. Applicants should apply online at the University’s careers site (https://jobs.hku.hk ) and upload the following documents: a cover letter; an up
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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