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the architecture of transport networks, their physical and developmental constraints, and their contribution to the overall fitness of the organisms they serve. Ultimately, we seek to integrate computation, theory
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-tier venues (e.g., ICSE, ASE, TOSEM, AAAI, EMSE), with at least 10+ publications, including multiple CORE A/A* papers. Demonstrated expertise in deep learning architectures, computer vision, and medical
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an advanced AI-augmented digital platform (AiCT-Med) powered by cutting edge machine learning models trained on multiple large, aged care datasets from providers across Australia. The platform is designed
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responsibilities in the project. Develop digital twins of the detailed electrical power system architectures of various e-vessels based on the concept design in real-time simulation environment such as OPAL-RT and
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, software development, and research experiments. Contribute to the development of working prototypes and demonstrations for mobile biometric systems utilizing federated learning architectures. Prepare
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Qualifications Research experience with unsupervised and weakly supervised CNN and RNN architectures such as GANs, contrastive Learning, multiple instance learning, and transformer models Experience with