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privacy-enhancing techniques such as secure multi-party computation, homomorphic encryption, differential privacy, and trusted execution to design algorithms and protocols to secure ML models within
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The United Nations Development Programme has identified access to information as an essential element to support poverty eradication. People living in poverty are often unable to access information
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for under Research Program. Application Close: Monday 10 August 2026, 11:55pm AEST Supporting a diverse workforce
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of Harm' as the scholarship you are applying for under Research Program. Applications Close: Monday 10 August 2026, 11:55pm AEST Supporting a diverse workforce
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. Participating in an overseas study program . This excludes the Global Immersion Guarantee. Living with a disability or medical condition. You must be registered with Disability Support Services . Benefits $3,000
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for computational analysis. This learning analytics project will be conducted in the context of simulation-based healthcare education, and it will support the development of effective strategies to improve teamwork
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Please note that this PhD topic is offered exclusively at our Monash Malaysia campus and is not available at the Clayton campus. Core PhD Question How can we design future medical AI systems that remain secure, privacy-preserving, explainable, and clinically reliable when exposed to adversarial...
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My research focuses on the dramatic final stages of massive stars, exploring how they end their lives as gamma-ray bursts, supernovae, and kilonovae. To unravel these mysteries, I employ a combination of multi-wavelength observational data with sophisticated simulations. I am a member of various...
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I am an ARC Future (former DECRA) Fellow and lead the Structured Nanophotonics Group at Monash University. My research in nanophotonics explores the full potential and multi-dimensional nature of light, focusing on controlled light-matter interactions at the nanoscale. Driven by the fascinating...
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Many machine learning (ML) approaches have been applied to biomedical data but without substantial applications due to the poor interpretability of models. Although ML approaches have shown promising results in building prediction models, they are typically data-centric, lack context, and work...