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stellar interiors, birth properties of black holes and neutron stars, supernova light curves and spectra, gravitational waves, neutrino astrophysics, the production of heavy elements stellar explosions, 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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of these crystals greatly affects the performance of the metal and hence the performance of components where metals are used - such as in aeroplanes, gas turbine engines, cars, etc. The manner in which such materials
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solution eleXsys as a core element operating autonomous microgrids of the future, as well as providing integrated Volt/VAR management, allowing for full two-way energy flow in the entire microgrid network
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to implement these new methods Lead and contribute to high-quality research publications Engage with interdisciplinary teams and stakeholders Contribute to mentoring, proposal development, and capacity building
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formula is true or false (EXPTIME vs NP). Can we develop and implement efficient algorithms for this problem? This problem has been attacked using multiple different methods for the past 40 years, without
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proven record of relevant teaching experience in a tertiary environment, including experience in developing teaching materials. A deep understanding of contemporary pedagogies and methods is essential
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of vulnerability. Arguably, cybersecurity scholars need to learn much more about the methods criminals employ to trick victims out of money. This PhD scholarship will extend upon Prof Whitty's work in this field
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in diverse, real-world environments. Both classical machine learning methods and deep learning techniques can be employed to tackle this task. This project aims to achieve several objectives: 1
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software frameworks, algorithms, robust testing and validation methods, and/or empirically validated solutions that contribute directly to social good, promoting trust, fairness, transparency, and