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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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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
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, interviews, digital methods) public attitudes and social dynamics (survey research, experiments, mixed methods) lived experience, reporting, and community/institutional responses (interviews, ethnography, case
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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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phenomenon that has the potential to shift an established photochemical paradigm. The research will involve a range of computer modelling methods and techniques in the areas of theoretical and computational
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I supervise computational projects in electron microscopy imaging for investigating materials at atomic resolution. Some projects centre on analysing experimental data acquired by experimental
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study flow dynamics relevant to reactor design using optical diagnosing methods, followed by image processing, which may include machine learning-based techniques. This suits Mechanical Engineering
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collections, polio memories, stories of regional Australia, and the introduction of vaccines. It also has a digital mapping component. The doctoral student in this project will have co-supervision from a member
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-time and/or external study is obtained as part of your admission process). Have a background in journalism, media and communication, justice or law. How to apply Apply for this scholarship at the same