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Skip to main content Main Menu - Primary Home Projects Supervisors Contact Testing AI/LLM systems Primary supervisor Yongqiang Tian Research area Software Engineering In this project, we will develop
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Skip to main content Main Menu - Primary Home Projects Supervisors Contact Automated software testing and debugging with/without LLMs Primary supervisor Yongqiang Tian Research area Software
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, research funding, scientific careers, collaboration, or the norms governing AI use. Projects may also use data from publications, citations or scientific careers to test the implications of a model
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Vakhitova, and Associate Professor Matteo Vergani. The project will establish Australia’s first national longitudinal cohort study of the drivers and consequences of Islamophobia. It will examine
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process rationalisation, as well as contribute to projects involving system development and testing. You’ll work with a broad range of stakeholders to improve efficiency, reduce costs and enhance
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primarily on low-cost, routine blood tests rather than complex diagnostic infrastructure. By enabling early identification and immediate routing of high-risk patients to specialized gynecologic oncologists
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conventional perception pipelines towards AI systems that can observe, remember, anticipate, and act. The project will examine questions around multimodal representation learning, temporal modelling, predictive
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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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and official grading system (if available), supported by scanned copies of relevant certified documentation English language proficiency test results (if applicable) Names and contact details of 2
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standards, testing strategies, automation, documentation and the adoption of emerging Microsoft technologies. This is a role where you can bring your expertise, influence meaningful change and help shape