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deep learning theory, Bayesian statistics, and generative modelling, this work will advance our understanding of both the capabilities and vulnerabilities of modern AI systems. This will have potential
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with digital twin modelling, remote sensing, and cloud computing is valued, as is a commitment to learning and advancing in these areas. The successful candidate will have the ability to work with large
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These models are technology platforms that facilitate drug discovery and fundamental research. Our research is funded by Australian Research Council. This project aims to develop bio-microfluidic
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materials, formulations and procedures to create particles, for outputs aligned with both academic advancement and industry partners. Materials will be evaluated for size, morphology and structure-function
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for construction waste grasping, and further design flexible and adaptable robotic grippers for waste handling. The existing commercial robotic hand and grippers might not be able to handle irregular and heavy
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include: REZ Long-Term Benefits: How can First Nations communities keep benefiting from Renewable Energy Zones after construction is completed? Rooftop Solar Challenges: What are the issues with installing
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samples. -Applying Gross's (2015) process model of emotion regulation to the understanding of ADHD. -Exploring the definition/structure of ADHD statistically, and whether emotion regulation problems should
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seismic data to produce 3D geophysical models that will constrain the subsurface extent of rock units that might be suitable for hydrogen generation via radiolysis and/or serpentinization and identify
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, HNMR, BET etc.) will be employed to characterize the carbon nanofiber structures. For molecular level, understanding, DFT modeling will be employed. The project would require fundamental investigations
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stiffness by changing their composition and self-assembly process. The relationship between nanoparticle structure and stiffness will be determined both through experimental and modelling approaches. Finally