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Field
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Qualifications Master or Honours About Swinburne University of Technology Swinburne’s strategy draws upon our understanding of future challenges. We choose to build Swinburne as the prototype of a new and
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Tomography (XCT), a non-destructive imaging technique, to perform crushing experiments of TRISO particles over a range of temperatures, thereby achieving a better understanding of the deformation behaviour
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contribute to research and policy addressing the escalating issue of the consumption of image-based sexual abuse (IBSA) and child sexual exploitation material (CSEM) online. The project is based at Flinders
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defects without compromising structural integrity, thus ensuring passenger safety and operational efficiency. The project aims to design and prototype a ground-based automated inspection system capable
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Biomedical Engineering conducts leading research in image analysis, computer vision, and machine learning, with a growing emphasis on generative AI and AI for scientific discovery. Our mission is to develop
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The rapid growth of the data economy and the privacy implications accompanying it have motivated a new paradigm shift towards decentralisation of data on the Web, which aims to foster data
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analysis methods. You will gain expertise in integrating experimental total scattering and high-resolution imaging data with artificial intelligence and atomistic simulation tools to overcome current
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research methods. Knowledge and interest in mental health and body image / appearance psychology. In light of the project’s service user and equity-focused orientation, we particularly welcome applications
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at the same time so special. The originality of the experiments is in the combination of X-ray based scattering and imaging methods to monitor the changes at the particle scale during testing. Research
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friction models. Integrating Experimental Data: Collaborate with experimental teams to incorporate data from calcium imaging, confocal microscopy, and high-resolution video recordings. Use experimental data