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challenging problem due to the limitations of classical algorithms. These methods often struggle with the complexity and scale of accurately predicting mRNA secondary structures. This pilot research project
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are undertaking research in aerospace engineering and specifically on the application of distributed propulsion systems on future aeroplanes. Project details: Despite being some of the most complex and efficient
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In NeuroDistSys (NDS): Optimized Distributed Training and Inference on Large-Scale Distributed Systems, we aim to design and implement cutting-edge techniques to optimize the training and inference
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for physics beyond general relativity with gravitational-waves" (with Prof Eric Thrane) "Improving the sensitivity of gravitational-wave detectors" (with Prof Eric Thrane) web page For further details
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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(Academic Level A) Based at our St Lucia Campus with fieldwork primarily in Palau About This Opportunity We invite applications from motivated Field Ecologists with expertise in mapping coral distributions
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My research explores ways to determine the atomic architecture of materials so we can understand and manipulate a material’s behaviour. At the atomic level, amazing and beautiful quantum phenomena can occur that are very different to the macroscopic world. Our group develops methods to measure...
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I supervise a wide range of PhD projects on experimental research into the electronic properties of novel quantum materials including topological insulators, graphene, and other atomically thin two-dimensional materials. I am interested in creating a low-power topological transistor, in which an...
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determined by combining the observed space density of galaxies, the measured spatial distribution of galaxies and simulations of the dark matter distribution. Example themes for student projects follow and
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healthcare application needs to analyze sensitive patient data across distributed nodes. Researchers and students can explore privacy-preserving algorithms and technologies like federated learning and zero