19 medical-image-processing-phd Fellowship positions at Hong Kong Polytechnic University
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School of Fashion and Textiles Postdoctoral Fellow / Research Associate / Research Assistant (Ref. 250711011) (1) Postdoctoral Fellow [Appointment period: twelve months] (2) Research Associate [Appointment period: twelve months] (3) Research Assistant [Appointment period: twelve...
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Department of Electrical and Electronic Engineering Postdoctoral Fellow / Research Associate (Full-time/Part-time) / Research Assistant (Full-time/Part-time) (Ref. 250708006) (1) Postdoctoral Fellow [Appointment period: six to twenty-four months] (2) Research Associate...
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project - “Point-of-Care artificial intelligence integrated internet-of-medical-thing (PoC-AIoMT) system for infection and fibrosis screening and comprehensive management for peritoneal dialysis
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projects on-time with minimum supervision. Preference will be given to those with research experience in machines designs and development of computer programmes for numerical computation of electromagnetic
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) strong background in quantitative methods, statistics, computer science, geospatial data analysis and modeling; (b) experience in AI and geospatial computer version; (c) advanced skills in scientific
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Research Centre for Chinese Medicine Innovation Senior Research Fellow (two posts) (Ref. 250408013) Duties The appointees will assist the project leader in the research project - “Research Centre for Chinese Medicine Innovation”. Qualifications Applicants should have a doctoral degree with at...
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Assistant, applicants should have an honours degree or an equivalent qualification. For all posts, applicants should have strong background in materials processing technologies, especially for light alloys
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) optimise BIM software performance and address challenges, including model processing, data storage, and rendering efficiency; and (e) collaborate with AI algorithm teams to understand the business
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research using methods such as sensing technique, 3D printing, human-computer interaction, simulation, and/or machine learning to address challenges in machinery motion planning and construction safety