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retrieve shapes, overlay errors, and other geometrical parameters of the target using methods ranging from local and global optimizers to priors and neural networks developed by partners in the project. Job
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improved using machine learning techniques. The developed techniques will be applied to metrology of semiconductor samples. Job requirements You are an enthusiastic candidates with a ‘drive’ for applied
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, educational and community-based processes that underlie typical and atypical developmental outcomes for children and young people, with a particular focus on developing evidence-based practice models of benefit
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multidisciplinary consortium brings together academic medical centres, universities, healthcare organisations and industry partners to develop and implement innovative technologies for home-based healthcare and
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Student Research Assistant will: Develop social media presence for a podcast. Increase the visibility of the podcast (to increase the number of listeners). With the eventual possibility to extend
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Hub) is an Australian research collaboration funded by the Australian Research Council (ARC) that brings together Australia's leading universities and industry partners to develop innovative
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at the intersection of wireless communications, networking, embedded systems, and satellite technologies. Your research will contribute to the development of reliable, resilient, and sustainable
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validation, digital twin frameworks are developed enabling a virtual assessment and optimisation of steel microstructures before they are produced. This programme is therefore essential for the future hydrogen
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computational fluid dynamics (CFD) simulations of blood flow through arteries and develop a cutting-edge super-resolution framework using convolutional neural networks (CNNs). The ultimate goal is to vastly
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development, integration of off-site manufacturing design and practices for deconstruction, productivity quantification, among others) to realize the potential benefits of off-site construction and automation