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. The start date is October 2025. Are you passionate about applying computational science to real-world engineering problems? Do you want to develop digital twins of materials that can predict performance and
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studies of aluminium precipitate evolution during forming; or development of solid‑state joining techniques for dissimilar lightweight metals. Prior research experience in materials processing
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sensor spoofing. These attacks manipulate input data while maintaining apparent operational normality, potentially leading to unsafe decisions without detection. This project aims to develop a novel
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if this is the case. As this is the methodology used by government to assess and compare the energy and environmental performance of dwellings, the current rating disincentivises developers from specifying
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reduce unsustainable costs?’ The research will include: Evaluating the initiatives already in place and being developed Reviewing how other places have solved similar issues Feeding back the above findings
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, and energy efficiency. Advanced Manufacturing: Developing and implementing cutting-edge fabrication techniques (e.g., micro-fabrication, polymer, nanoparticle) to realise the designed metamaterial
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validated surface functionalisation methods that significantly improve metascintillator performance, accelerating the development of advanced radiation detectors for ToF-PET and enhancing early cancer
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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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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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine