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prediction, signal tracking, fluid dynamics, and space exploration. Advancing Signal Modelling with Physics-Informed Neural Networks This project aims to develop Physics Informed Neural Networks (PINNs
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serious threat to aquatic ecosystems and degrade surface and groundwater quality. Yet, the geochemical controls governing dissolved aluminium at low pH remain poorly understood. This Australian Research
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the development of predictive models to anticipate potential failures. Additionally, the project will facilitate the transfer of this technology to industry, while also advancing academic knowledge
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world-class orthopaedic devices being used globally. Project outline PROFNUL 2 The successful candidates will be embedded into a randomised control trial investigating if there are differences in hip
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augmentations such as project energy connect, Humelink, Marinus Link ETC Lack of available accurate generator and reinforcement models Protection and emergency control scheme modelling challenges. The research
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to hydrogen production in continental interiors? What is the role of fault and fracture-related permeability in the transport of hydrogen within Earth’s crust? What are the key geological controls
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), mouse models, fluorescence microscopy (confocal), genomics, epigenetics, cell biology and biochemistry techniques (e.g., RNA/ChIP-seq, mass spectrometry). Successful track record in conducting and driving
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, this project will Investigate current DES(s) on “controlled” mixed battery chemistries; specifically NMC:LFP ratios. It will also develop an extraction process to optimally recover metals from NMC:LFP black mass
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of the role of chromatin in development and diseases like cancer. We seek a highly motivated, creative scientist to spearhead a project using stem cell and models to address a fundamental question in chromatin
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well as an informed understanding of the losses that have already occurred. If possible, the project could extend to predicting (based on past experience) which portions of the Adelaide Park Lands might be most at risk