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to contribute to research on hybrid numerical-exponential asymptotic methods and their applications at the University of Sydney Base Salary, Academic level A $105,117 - $121,054 p.a + 17% superannuation About the
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to the development of new concepts, methods, and scalable systems for networked digital twins that support autonomous decision infrastructure for adaptive action with human oversight. This project is part of
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methods (for example, learning-based, network-based, or agent-based approaches) to analyse dynamic decision behaviour, rather than focusing solely on predictive or optimisation performance prepare and
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-in, and performance or creativity degradation in socio-technical decision processes design and implement quantitative methods (for example, learning-based, network-based, or agent-based approaches
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collection and management for research, as well as basic knowledge of both quantitative and qualitative data analysis principles. Demonstrate high levels of computer literacy, including proficiency in learning