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sources of evidence such as audio, physiological activity and characteristics of the students). This project aims to develop methods for supporting teachers in reflecting on their positioning strategies in
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significant research program funded by the Australian Research Council Discovery Project titled “Discovering the sustainable size of cities”. This interdisciplinary project investigates how high-speed rail (HSR
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(Honours) program. This student-centred course is designed to prepare graduates for meaningful, person-focused practice. You will lead and support teaching in areas that explore the psychological and
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operators for these notions. Over the past fifty years, such non-classical logics have proved vital in computer science and logic-based artificial intelligence: after all, any intelligent agent must be able
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PhD Scholarship in Digital Mapping of Homemade & DIY Cultural Economies in First Nations Communities
, and grassroots creativity that may be undervalued in formal cultural economies The project will innovate methodologically (leveraging methods from human-centred design and digital sociology) to generate
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package should be prioritised are surprisingly difficult computational tasks. State-of-the-art high-performance algorithms are used to calculate routes for the vehicles in order to minimise costs and
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Anomaly detection methods address the need for automatic detection of unusual events with applications in cybersecurity. This project aims to address the efficacy of existing models when applied
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members. This initiative provides students with the opportunity to apply independent thinking and problem-solving skills to develop or enhance products, methods, or services. Projects may be self-contained
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: pro-rata $120,138 - $132,610 + 17% superannuation The mitoHOPE program is seeking a communications specialist to support program research and operational outcomes. Central to the role will be
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anomalies in evolving graphs. In this research proposal, our aim is to explore the parallels of deep learning and anomaly detection in dynamic graphs. In particular we are interested to redesign deep neural