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[Malaysia Campus- VPSSP] An AI-Informed Planetary Health Framework for Equitable AMR Risk Mitigation
This project develops an AI-informed, community-grounded framework to understand and mitigate antimicrobial resistance (AMR) risks within a planetary health context. Building on the risk modelling
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PhD Scholarship - Energy-Efficient Decentralised Training Frameworks for Large-Scale AI Models on Geo-Distributed Infrastructure Job No.: 696617 Location: Clayton campus Employment Type: Full-time
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evaluation, the project seeks to develop privacy-preserving frameworks, security benchmarks, and design guidelines that enable trustworthy, user-centric digital credential ecosystems.
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language models (LLMs) to address these challenges by developing a comprehensive framework that seamlessly integrates LLM capabilities for generating accurate and optimised code, constructing complex SQL
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conditions (low back pain and diabetes). It will then co-create a theory-driven, evidence-based assessment rubric that will form the foundation of an online framework for assessing the reliability
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guarantees of FL. In this project, we aim at an ambitious goal - designing secure and privacy-enhancing algorithms and framework for FL and applying our designs into real-world applications. To achieve
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Digital health (DH) technologies promise significant improvements in healthcare delivery, but their successful implementation requires rigorous evaluation to ensure they meet clinical and operational needs. There is a key opportunity for specialist work in an emergent intersection area which we...
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Scholarship in CSIRO Industry PhD Program - Project 2: Techniques and Frameworks for Enabling Post-Quantum Cryptography (PQC) Migration Job No.: 678538 Location: Clayton campus Employment Type: Full
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. This study aims to construct a transparent, non-invasive predictive framework combining machine learning and explainable AI (XAI) to differentiate malignant from benign pelvic masses, stratify patient risk
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are available. Expected Contribution The research aims to develop a robust, interpretable and generalisable AI framework for cardiovascular risk prediction and clinical decision support. The study will consider