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a cross-disciplinary School of Computing and Data Science, the University is committed to fostering interdisciplinary exchange with an outlook for transformative breakthroughs, innovations and global
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goals Identify and integrate emerging technologies (e.g. cloud computing, AI and data analytics) to optimize university operations and user experiences Stakeholder Engagement: Collaborate with academic
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to: biomedical science and engineering veterinary science computer science and data science neuroscience and neural engineering bio-statistics and AI-healthcare smart/semi-conductor manufacturing AI/robotics
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- “Advanced computational approaches for calcaneal fracture management: integrating 3D modelling, deep learning, and reinforcement learning”. Qualifications Applicants should be form five school leaver with
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computational biology expertise to analyze complex datasets ensure compliance with ethical and regulatory requirements for clinical research provide leadership and mentorship to junior researchers collaborate
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Duties Provide teaching support for course teachers; Support course administration and development of teaching materials; Grade student assignments; Assist in programme administration including
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interdisciplinary areas. Research fields of particular interest include, but not limited to: biomedical science and engineering veterinary science computer science and data science neuroscience and neural
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interdisciplinary areas. Research fields of particular interest include, but not limited to: biomedical science and engineering veterinary science computer science and data science neuroscience and neural
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activities; (b) support academic programme management; (c) organise research events and experiential learning activities (e.g., conferences, seminars and student field trips); (d) play a liaison role between
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interdisciplinary areas. Research fields of particular interest include, but not limited to: biomedical science and engineering veterinary science computer science and data science neuroscience and neural