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produced, ‘is this image part of a series’, and/or ‘have we seen an image from a similar place or time before’? This inference needs to be done by extraction and recognition of relevant features from
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We have a range of potential research projects on offer in partnership with VIFM - https://www.vifm.org/ - looking at ML techniques in predicting forensic diagnoses / image analysis, across
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the area of end-to-end modular autonomous driving using computer vison and deep learning methods. This includes developing an efficient and interpretable image processing, vision-based perception and
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Machine learning has recently made significant progress for medical imaging applications including image segmentation, enhancement, and reconstruction. Funded as an Australian Research Council
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in conventional imaging, and to access a complementary ‘dark-field’ signal that originates from tiny sample structures. We do this by designing and implementing novel experimental set-ups and
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I am an experimental particle physicist and I specialise in the study of particles containing the beauty and charm quarks. My research aims to help improve our understanding our universe by comparing our experimental observations to predictions made using the Standard Model of Particle...
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theoretical colleagues. All research takes place within our dynamic particle physics research group with academics and postdocs, as well as graduate and undergraduate students. Some work will be purely
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known as Team COMPAS -- includes a number of amazing undergraduate and graduate students, postdocs, alumni, and other fantastic collaborators. Please contact me if you are interested in joining our group
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to life in breakthrough experiments—please reach out. "Quantum nanophotonic chips" "Structured-light imaging and spectroscopy” “Meta-optics and meta-waveguides" "2D materials and Lightwave valleytronics
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Indigenous Health Education Positions Job No.: 636959 Location: Clayton, Caulfield or Peninsula campus Employment Type: Full-time Duration: 3-year fixed-term appointment Remuneration: $114,951