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limited to: biomedical science and engineering veterinary science computer science and data science neuroscience and neural engineering bio-statistics and AI-healthcare smart/semi-conductor
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intelligence and machine learning in mental health, big data analytics, and pharmacoepidemiology. Applicants who adopt multidisciplinary approaches to address key challenges in psychiatry and mental health
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applying cutting-edge computational and quantitative methods in social sciences, such as artificial intelligence (AI) and big data. The candidate should have a proven ability to work on cross-disciplinary
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or Computer Science, Artificial Intelligence and Data Analytics, Language/Education Technologies, Digital Humanities, or a related discipline, with at least three years of relevant experience; (b) demonstrate a
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the tertiary education sector; (d) possess advanced skills in large-scale data management and analysis, with proficiency in Microsoft Excel (e.g., advanced formulas, pivot tables, data visualisation) and other
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given to those with expertise in big data analytics, business statistics, econometrics, data-mining, operations management, operations research, optimization, statistics in healthcare management, supply
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big data analytics, to drive innovation and digital transformation in alignment with the University’s Strategic Plan; (b) formulate and implement cutting-edge and innovative IT strategies, policies
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on finding, using and managing information effectively, including using AI tools for learning and research; (b) develop the Library’s information literacy programmes, actively collaborating with Faculty
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least eight years of solid and relevant post-qualification experience at a supervisory level, preferably gained from large organisations; (c) great adaptability and a strong sense of ownership in
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Research Assistant [Appointment period: twelve months] Duties The appointees will assist the project leader in the research project - “Rethinking road safety risk evaluation by leveraging big mobility data