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important across different industries. To reduce the carbon footprint of power transformers, a complete life cycle assessment (LCA) including raw materials, design, manufacture, transport, operation
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) under the supervision of Dr. Elina Spyrou . Summary of Project: Power systems are at the core of the transition to net-zero energy systems, and they have to transform in two ways. First, their generation
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from building-integrated photovoltaics to solar-powered greenhouses and aerospace technologies. However, despite significant progress, OPVs still face limitations in long-term operational stability
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penetration of renewable energy sources, power systems face growing challenges related to transmission bottlenecks, fluctuating power flows, and grid congestion. Phase Shifting Transformers (PSTs) are vital in
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machine learning frameworks such as recurrent neural networks and transformers. Models and datasets will be studied and benchmarked in key tasks relating to both prediction/forecasting and anomaly detection
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public-facing cultural programme. It offers the opportunity to develop a unique curatorial approach that engages with Gloucester’s civic transformation, supports the University’s strategic goals, and
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neural networks and transformers. Models and datasets will be studied and benchmarked in key tasks relating to both prediction/forecasting and anomaly detection. Comparison with known analytic methods and
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provides essential sealing solutions for industries ranging from energy to pharmaceuticals. Ready to Join? Take your career to the next level by applying for this transformative PhD opportunity! For more
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development opportunities. The University of Melbourne We take pride in our people, who all contribute to our mission to benefit society through the transformative impact of education and research. Discover
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Digital-Twin Technology to Accelerate Development of Electric Propulsion Systems This exciting opportunity is based within the Power Electronics, Machine and Control Research Institute at Faculty