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following cycles caused by changes in chemistry and hydrogen bond donor (HBD) composition. DES also exhibits poor chemical stability at higher operating conditions, resulting in solvent loss. Furthermore
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data requirements, and lower costs for large-scale modelling tasks. PINNs enhance predictive capabilities and efficiency by combining data-driven methods with physical principles. Unlike traditional
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of herbicide resistance transfer in weeds. The student will work in a vibrant, multi-disciplinary team and develop skills in biochemistry, molecular biology and plant science. The findings from
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the hydrodynamic loads generated by large-scale wave energy devices. This project is a collaborative effort, with joint supervision from Dr. Nataliia Sergiienko at the University of Adelaide and colleagues
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the responsibility for the big shift to decarbonisation. We have the scale to make a difference and seek new, low-carbon technologies and methods that will overcome barriers and help transition the steel, iron