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approaches. Apply hybrid optimisation techniques (e.g., quantum-inspired or QAOA-based methods) to determine optimal intervention strategies under resource constraints. Compare the performance, scalability
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-route tasks to maintain uninterrupted service. This research area involves developing fault-tolerant systems that adapt to hardware and software failures. Students will work on predictive maintenance and
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is highly complex. For the proposed PhD project, experimental data are already available that bring together maps of orientations of such crystals together with the deformation pattern generated during
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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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Skip to main content Main Menu - Primary Home Projects Supervisors Expression of Interest Contact Interoperability (using FHIR) in cutting-edge medical software systems Primary supervisor Chris Bain
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The Australian Research Council (ARC) Training Centre in Optimisation Technologies, Integrated Methodologies, and Applications (OPTIMA) is seeking applications for ten ARC fully-funded PhD projects
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time. In this project, we propose a method for identifying and classifying such emerging asynchronous trends. The goal is to be able to predict how a new emerging trend will develop using similar
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Statistical Methods, Automated Planning and/or Reinforcement Learning.
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Automating code generation, SQL query formulation, and data preprocessing pipelines is a crucial step toward intelligent and efficient software development. This project aims to leverage large
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AI is now trending, and impacting diverse application domains beyond IT, from education (chatGPT) to natural sciences (protein analysis) to social media. This PhD research focuses on the fusing AI