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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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Current reseach is in the areas of: Development of biomimetic structures as ultrasound contrast agents Deep tissue imaging using photoacoustic contrast agents All optical photoacoustic sensors
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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Artificial Intelligence (AI) is revolutionizing the field of Magnetic Resonance Imaging (MRI) by enabling faster, more accurate, and cost-effective image reconstruction. This project explores
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Job no:520488 Work type:Full Time Location:Crawley, QEII Medical Centre / SCGH Categories:Research support Be part of a national initiative advancing clinical imaging research. Drive innovation in
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The brain is a complex system and monitoring and imaging methods to observe critical neurophysiological variables underlying brain function are limited. This project works at the intersection
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School of Molecular Sciences ARC Centre of Excellence in Plants for Space Integrate advanced cell imaging and synthetic biology to create and characterise the first fully artificial plant chromosome
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School of Molecular Sciences ARC Centre of Excellence in Plants for Space Integrate advanced cell imaging and synthetic biology to create and characterise the first fully artificial plant chromosome
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of senior researchers, engineers, postdocs, and PhD students working together toward impactful science and mutual growth. In this role, you will apply your expertise in aquatic biogeochemical and ecological
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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