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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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algorithms to achieve real-time control and process optimisation of drainage pipe networks. It seeks to improve the operational efficiency of urban wastewater systems, reducing energy consumption and extending
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will undergo an interview process. If supported to apply, you will then submit an expression of interest (EOI) following the advice at how to apply for a research degree . In your EOI, nominate Dr
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new x-ray imaging techniques from the synchrotron to the laboratory Transforming breast cancer imaging with x-ray phase contrast Webpage: https://xrayimagingmonash.wordpress.com/ For further details
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-field imaging of dynamic processes" "Multi-scale X-ray speckle-based imaging" "Spectral X-ray speckle-based imaging" "Single-shot multi-projection X-ray phase-contrast imaging" "X-ray virtual histology
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policy. It will involve expert workshops, and stakeholder engagement. BACKGROUND Forest restoration is a critical strategy for mitigating the global climate and biodiversity crises. The process of
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" "Machine-learning-based imaging processing" webpage For further details or alternative opportunities, please contact: haoran.ren@monash.edu.
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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Conventional x-ray imaging is firmly established as an invaluable tool in medicine, security, research and manufacturing. However, conventional methods extract only a fraction of the sample
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approach that ensures both stealth and functionality. This project proposes to develop Stealth Integrated Sensing and Communication (Stealth-ISAC), a paradigm where communication and sensing signals remain