37 phd-in-computer-vision-and-machine-learning Fellowship positions at Hong Kong Polytechnic University
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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
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application; (b) experience in conducting human neuroscience research and/or be proficient in computer programming, e.g. Matlab and Python; (c) a good command of both written and spoken English; and (d
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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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machine learning methods, particularly large language models (LLMs), to marketing research. Applicants are invited to contact Prof. Edward Lai at telephone number 2766 7141 or via email at edward-yh.lai
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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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and energy materials. Preference will be given to those with knowledge of computer programming, AI or machining learning. Applicants are invited to contact Prof. Jianguo Lin at telephone number 2766
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Department of Health Technology and Informatics Postdoctoral Fellow (Ref. 250703002) [Appointment period: twelve to twenty-four months] Duties The appointee will assist the project leader in
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posts) [Appointment period: each for twelve months] Duties The appointees will assist the project leader in the research project - “Auto-calibrated real-time locating service-based production logistics
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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
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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