25 parallel-processing-bioinformatics positions at Hong Kong Polytechnic University in Hong Kong
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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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to ensure smooth operation and accessibility for staff; (b) support training, stakeholder communication and preparation of project deliverables to promote system adoption and usability; (c) assist in
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- “Establishment of the PolyU-DRRC novel material science and technology innovation centre”. He/She will be required to: (a) prepare and process textile data for AI training; and (b) perform any other duties
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) have good computer literacy; (e) have good interpersonal and organisational skills; and (f) be a good team player and be able to work independently. Prior experience in organising student
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interdisciplinary collaboration. It will identify key challenges, including the systematic documentation of iterative processes and the validation of creative outputs as contributions to research. The appointees
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interfaces using functional and programmable materials; (b) collaborate on interdisciplinary projects bridging design, engineering and human-computer interaction; (c) publish research findings in high
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should have relevant experience in research and coordination work. Preference will be given to those with good publication records, experience in data processing, demand analysis, and SharePoint
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, Computer Science and must have no more than five years of post-qualification experience at the time of application; (b) have research experience in multimodal data fusion, video / image processing, and structural
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project - “Deep learning-based approach for process parameter optimization of SiC wafer under limited data”. He/She will carry out research in the areas of machine learning and data science, and also be
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VR-based tasks to study user cognition and creative performance; • process and analyse EEG data using advanced signal processing and machine learning techniques; • evaluate cognitive load