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7) Based at our St Lucia Campus - Brisbane About This Opportunity We are offering a great opportunity for a Supervisor, Engagement, Communication and Outreach who will contribute to the development
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University of New South Wales | Canberra, Australian Capital Territory | Australia | about 22 hours ago
in an effective manner, using appropriate guidance, motivation and development/coaching to ensure staff are supported to do their best work. At level 6 (in addition to level 5 above): • A demonstrated
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function, responsible for the design and development of key frameworks, tools, programs and processes in the areas of leadership, culture, development, talent and wellbeing which will ensure that UNSW staff
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, improving and transforming lives through excellence in research, outstanding education and a commitment to advancing a just society. Why your role matters The Head of Data Platforms leads the development and
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for this position. Candidates must hold unrestricted work rights to be considered for this position. Position Summary: The Practice Manager leads the overall operation and strategic development of the UNSW Lifestyle
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, contributing to impactful outcomes in the field. Supervision and Researcher Development: Support and mentor Honours and HDR students, while contributing to team development, recruitment, and performance
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actively involved in the development, curriculum design, and teaching in the Undergraduate Mental Health and Counselling Major within the Bachelor of Psychology and Bachelor of Health Sciences Courses. About
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development and monitoring of Transnational Education (TNE) initiatives to ensure alignment with the University Global Strategy’s operational and strategic goals. Oversee the end-to-end delivery of TNE projects
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the development of Explainable AI Systems that can provide explanations of AI agent decisions to human users. Past work on plan explanations primarily focused on explaining the correctness and validity of plans. In
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of the development of connections in these biological neural networks and their spontaneous and stimulation-driven formation. These models will provide a framework for simulating and testing biological neural networks