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This project will investigate artificial intelligence (AI) to improve weather forecasts and use crop models for making better farming decisions. The expected outcome is protocols for integrating AI
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. This process operates under ambient conditions, utilises water as a hydrogen source, and is powered by renewable electricity. Recent advances in electrocatalyst design – enabled by operando spectroscopic
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city size framework into dynamic land use–transport interaction (LUTI) models to enable scenario-based forecasting and planning under different infrastructure and policy conditions. Understanding
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Martin Australia invite applications for a project under this program, exploring the development of Physics Informed Neural Networks (PINNs) for efficient signal modelling in areas such as weather
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university research into commercial outcomes. Under this program, PhD students will gain unique skills to focus on impact-driven research. This Project aims to develop a predictive machine learning model
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Optimizing a 3D microfluidic IVD model to study cell responses to wear particles, refining culture conditions, and analysing cytotoxic and inflammatory mechanisms. Optimizing a 3D microfluidic IVD
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. This position will focus on one key stream: understanding and improving the interaction between EVs and roadside barriers. This will involve: Modelling EV crash dynamics with conventional and SRB barriers
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underwater communications is necessary. Conventional approaches in underwater communications only develop fixed models based on human knowledge or understanding which cannot fully cover the highly dynamic and
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conditions have been satisfied. Project description/summary: This Project will develop a model of material dynamics and heat transfer within a commercial vertical induction heating reactor. This novel reactor
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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