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sustainability. This PhD project aims to develop new ionic conducting materials as next-generation membrane alternatives for fuel cell and electrolyser applications. Ceramic ion conductors present a promising
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by understanding how cancer risk prediction models are influenced by missing and incomplete symptom data recorded in electronic health records (EHRs) and developing methods to address any issues
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to the development of a Bio-Integrated Liberation and Extraction (BILE) platform that combines electrochemical activation of lithium-bearing clays with biologically derived extraction systems. Within this broader
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will develop an integrated framework combining computational fluid dynamics (CFD) with quantum gas LiDAR measurements to improve the quantification of methane emissions. The central research question is
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both individual decision-making and multi-agent cooperation. The student will investigate two complementary directions: ToM-Enhanced Decision-Making for Autonomous Agents: Develop decision-making
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with NEOM, one of the world’s largest ecological restoration programmes, the project will develop machine-learning approaches to analyse satellite observations of vegetation change and evaluate large
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can solve. While conventional electronic information processors are exceedingly well-developed, their capabilities are being rapidly outstripped by the rapid rise of AI: both the training and inference
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. This PhD project aims to develop efficient, reasoning-enhanced Vision–Language Models tailored to multimodal medical data. The main aim is to investigate how explicit clinical reasoning can be embedded
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access to amenities, active travel opportunities, and health-promoting environments. This project will empirically test both assumptions to develop a more nuanced, evidence-based framework linking chrono
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VR simulations of surgical tasks developed in collaboration with our industry partner, FundamentalXR, adapted to be delivered with and without haptic cues. Then, at UQ the candidate will work with