10 parallel-processing-bioinformatics Fellowship positions at Hong Kong Polytechnic University
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posts) [Appointment period: each for twelve months] Duties The appointees will assist the project leader in the research project - “Study on design and analysis of high-performance parallel manipulators
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] Duties The appointees will assist the project leader in the research project - “AI-XR empowered computer-assisted surgery via effective fusion of empirical knowledge, human interaction, and machine
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supervise data collection and analysis; (c) assist in liaising with collaborators and managing the project procedure; and (d) perform any other duties as assigned by the project leader or her delegates
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) through advanced computer vision and LVLM integration; (b) overcome technical challenges: innovate solutions for large-scale small-object detection, dynamic lighting adaptation, and edge-computing
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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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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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The appointees will assist the project leader in the research project - “Research centre for non-invasive brain computer interface”. Qualifications For the post of Postdoctoral Fellow, applicants should have a
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(Full-time/Part-time) (two posts) [Appointment period: each for twenty-four to thirty-six months] Duties The appointees will assist the project leader in the research project - “Materials processing
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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