86 distributed-systems-networks-phd Fellowship research jobs at Hong Kong Polytechnic University in Hong Kong
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appointment] Duties The appointees will assist the project leader in the research project - “The role of the human frontopolar cortex in complex decision making: Neural network modelling, aging, and enhancement
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- “Fiber route estimation for optical networks in metropolitan areas based on DAS signal analysis”. Qualifications Applicants should have a doctoral degree plus at least three years of postdoctoral research
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project - “Advanced integrated co-packaged optics transceiver module for high-speed network applications”. Qualifications Applicants should have a doctoral degree or an equivalent qualification and must
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the research project - “White adipose tissue (fat) dysfunction in ageing and its related metabolic diseases: new insight and therapeutic intervention”. Qualifications Applicants should have: (a) a PhD degree
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progress deviation monitoring system (ACPDM) based on mobile mapping system”. He/She will be required to: (a) participate in the design, development and maintenance of BIM software or plugins; (b
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: Optical-fiber-based artificial compound eyes for 3D vision”. Qualifications Applicants for the Postdoctoral Fellow post should have a (i) PhD degree in Physics, Materials or Engineering and must have no
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for the Postdoctoral Fellow post should have (i) a PhD degree in Physics, Materials or Engineering and must have no more than five years of post-qualification experience at the time of application; and (ii) at least
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”. Qualifications Applicants should: (a) have a PhD degree in Remote Sensing, Geomatics, GIS, Computer Science, Photogrammetry or a related field, and must have no more than five years of post-qualification
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. For part-time appointment, the remuneration rate is HK$385 per hour. Consideration of applications will commence on 28 August 2025 until the position is filled. Apply Now Posting date: 22 August 2025
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health monitoring, preferably with a publication record in top-tier journals; and (c) be proficient in mainstream research frameworks for deep learning and computer vision. Applicants are invited