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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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human-computer interaction, as well as participate in the full range of faculty responsibilities, including scholarly research and service to the University. Applicants should possess a PhD or master
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or computer modelling software, such as R. They should have an excellent command of written and spoken English and a demonstrated record of publishing academic research papers. They should be organized, self
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analysis, and proficiency in statistical and computer modelling software (e.g. R, Python, Matlab, and C++) would be advantageous. The appointee will work with a research team to study the methodologies
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research areas in Computer Science, Artificial Intelligence, Data Science or a related field, including but not limited to: AI / IoT / AIoT Security; Computer Vision; Computing & Big Data Systems; Data
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/ AIoT Security; Computer Vision; Computing & Big Data Systems; Data Analytics & Technologies; Data Privacy; Digital Forensics; FinTech; Generative AI; Large Language Models; Theoretical Computer Science
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, preferably in a higher education setting; (c) have good knowledge and skills in quantitative and qualitative data analysis using relevant computer software and applications such as SPSS, MaxQDA and NVivo
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/ AIoT Security; Computer Vision; Computing & Big Data Systems; Data Analytics & Technologies; Data Privacy; Digital Forensics; FinTech; Generative AI; Large Language Models; Theoretical Computer Science
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infectious disease data using statistical and/or mathematical approaches would be highly desirable. Experience in statistical analysis, and proficiency in statistical and computer modelling software (e.g. R
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required to: (a) undertake specific research project(s) under the guidance of a project leader and contribute to the development of research activities; (b) develop computer programs to assess and