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prediction accuracy in the Australian National Electricity Market. Reinforcement learning for accurate, online price prediction in the Australian National Electricity Market Project summary This project will
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prediction, signal tracking, fluid dynamics, and space exploration. Advancing Signal Modelling with Physics-Informed Neural Networks This project aims to develop Physics Informed Neural Networks (PINNs
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will aim to develop novel tools to aid surgical fixation or predict complications and outcomes. Each PhD student will be expected to develop innovative solutions to the problem and publish approx. 3-4
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of scholarships: One Contact person: Dr Mario Fruzangohar (mario.fruzangohar@adelaide.edu.au ) Project 3: Improving genomic prediction accuracy using causal machine learning approaches Summary: Traditional genomic
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well as an informed understanding of the losses that have already occurred. If possible, the project could extend to predicting (based on past experience) which portions of the Adelaide Park Lands might be most at risk
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approaches to modelling CO2 injectivity. The successful candidate will work with researchers at the University of Adelaide and Shell Global Solutions to develop an analytical tool that predicts the nature