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are supported by quantum mechanical theoretical formalisms. Our fundamental findings yield promise for future applications in electronics, optoelectronics, spintronics, information processing and storage, sensing
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I am an experimental particle physicist and I specialise in the study of particles containing the beauty and charm quarks. My research aims to help improve our understanding our universe by comparing our experimental observations to predictions made using the Standard Model of Particle...
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-offs between the modularity (henceforth interpretability) and the efficiency in existing end-to-end modular autonomous driving models. In this PhD project, student is expected to conduct research in
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, mainly in the area of search-based software testing to verify that the AI components of self-driving cars work as they should. This project is in collaboration with Professor Hai Vu and the Monash
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This project is technical in nature and would suit a candidate with a background and interest in #Java programming, health informatics or health data (or a combination thereof). The primary aim of this work is the extend and localise (to the Australian context) the open source Synthea stack ....
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measurements in particle physics. Many of my projects are informed directly by current measurements, e.g. addressing new or unexpected features seen in the data. Others focus on improving the formal accuracy
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I am seeking PhD candidates interested in working on designing Learning Analytics innovations to study classroom proxemics by analysing and visualising indoor positioning data (along with other
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projects that involve data analysis, the application of artificial intelligence, the development of new detection techniques, and the exploration of new experimental methods through collaboration with our
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possess translational symmetry, the role of structure and symmetry in glasses is not established. This research programme involves the development of new x-ray and electron diffraction-based methods
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the shortcomings of these techniques, deep learning is more and more involved in static vulnerability localization and improving fuzzing efficiency. This project aims to deliver a smart software vulnerability