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MD-PhD Industry Leaders Scholarship (for returning MD-PhD students) Industry Leaders Scholarship This scholarship is awarded to Monash University medical students who have demonstrated a commitment
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: $37,145 pa pro rata tax exempt stipend The Opportunity Monash University is offering a fully funded PhD scholarship for a motivated candidate interested in intergenerational play and wellbeing. The project
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This Masters or PhD project aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain ML predictions and
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PhD Scholarship 2026 – Neonatal brain injury and neurodevelopmental follow-up Job No.: 691299 Location: Department of paediatrics, Monash University and Monash Newborn, Monash Children’s Hospital
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I supervise projects in particle physics. My main emphasis is on phenomenology, comparison of predictions with experimental measurements. I follow developments in flavour physics: weak decays of mesons and baryons and their role as indirect probes for physics beyond the standard model. I also...
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research. About Monash University At Monash , work feels different. There’s a sense of belonging, from contributing to something ground breaking – a place where great things happen. We value difference and
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Cybersecurity is an interdisciplinary field. There is an urgent need to build up talent in human factors in cybersecurity. This PhD will provide the candidate with a unique pathway into industry
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We have several PhD opportunities available in areas such as Multimodal Large Language Models (MLLM) for human understanding, MLLM safety, and Generative AI. If you have published in top-tier
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cyberbullying compared to 17.75% of nonsexually abused girls. There are also high rates of other criminal activities observed in social medias, such as scams, fraud and intellectual property crimes. This PhD
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We are seeking a motivated PhD candidate to work on unsupervised music emotion tagging within the broader field of affective computing. The project aims to develop reproducible machine learning