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response incentive arrangements with the national electricity market (NEM). Currently cost recovery for regulation frequency services is based on the causer pays process, which allocates the cost of sourcing
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an exciting PhD scholarship to tackle one of the most pressing environmental challenges—detecting methane emissions from space using advanced neural network technology. This unique opportunity is part of
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and it involves a large number of computational operations. A network simplification approach will be designed to slim network sizes to suit real time implementations. Robust underwater acoustic
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their full leadership potential and help them gain exposure to Australia’s national energy industry. The prestigious PhD scholarship opportunity will empower you to build on your passion, gain exposure, and
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for policy, practice and advocacy. The mixed-methods project will use a combination of participatory approaches including but not limited to GIS mapping, stakeholder analysis, network and systems mapping
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opportunities to join the Curtin enAble Institute’s EMCR network that offers mentoring, research capacity building and professional development opportunities to HDRs and early career researchers. They will be
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student to join a cutting-edge project led by Professor Xia-Ji Liu, funded by the Australian Research Council. This position offers the chance to work at the forefront of theoretical physics at the Centre
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open-source tools and training modules for global utility adoption. The framework combines physics-informed graph-neural-networks (GNNs), diffusion model, and explainable reinforcement learning (XRL
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investigate the optimal methods for combining multi-satellite InSAR with a network of Kurloo GNSS devices to provide robust 3D ground motion monitoring from space. The potential benefits may include
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protein/enzyme preservation, thermal stability, and controlled release, targeting biomedical, enzymatic, food additive, environmental, and packaging applications. Project Overview: The research integrates