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federated learning and multimodal deep learning models for healthcare. The project will focus on enabling privacy-preserving learning from distributed healthcare data sources, including longitudinal medical
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PhD Scholarship Opportunity - Processing intelligence for green metals using in situ X-ray characterisation and machine learning Job No.: 693787 Location: Clayton campus Employment Type: Full-time
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experience, deemed equivalent by the GRC (or delegate). The ideal PhD candidate will have: A strong background in machine learning, deep learning, and signal processing Proficiency in Python and machine
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should ideally have experience in: Essential Deep learning and machine learning Computer vision Python programming PyTorch or TensorFlow Strong mathematical and analytical skills Desirable Video
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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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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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the most interesting thermonuclear reactions occur deep in their interiors; the red giant phase is also when stars are more likely to interact with a gravitionally bound companion, if they have one! Students
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motivation Testing whether the system performs equitably across cultural and language groups Training spans intervention design, trial methodology, human-computer interaction, and applied machine learning
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learning of Japanese in Australia. The MJLEH Scholarships support graduate researchers to complete a PhD at Monash University on a topic related to the acquisition and/or teaching of Japanese Language and