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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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computers, and especially fault-tolerant quantum computers, for high-value decarbonisation use cases such as improved battery chemistries, the development of new catalysts for hydrogen, biofuel or ammonia
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group to work on a project developing provable network security methods that use higher-order graph-based abstractions to model networks and network security problems. Scalable algorithms developed
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the use of quantum computers, and especially fault-tolerant quantum computers, for high-value decarbonisation use cases such as improved battery chemistries, the development of new catalysts for hydrogen
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Federated learning (FL) is an emerging machine learning paradium to enable distributed clients (e.g., mobile devices) to jointly train a machine learning model without pooling their raw data into a
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who likes building things and can integrate systems to help develop both robotic and perception platforms. We’re offering this role as a hybrid position as part of QUT’s commitment to embracing
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applications for monitoring individuals' health, activities and social behaviour. Yet, there is a lack of common and standard guidelines in developing mobile sensing apps (from both software development and UI
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automated recovery algorithms, improving system resilience. Research Areas for Master’s and PhD Students AI-Enhanced Resource Forecasting and Optimization: Research Focus: Developing and testing ML algorithms
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active research interests in quantum computing, quantum algorithm/software development and applications in decarbonisation who can take full advantage of the unique opportunities the QDA provides
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at Griffith University. We are seeking applicants with active research interests in quantum computing, quantum algorithm/software development and applications in decarbonisation who can take full advantage