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modelling and simulation of transmission and distribution networks, including benchmarking data models, developing optimal power flow algorithms, and creating state estimation and multi-energy optimisation
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fabrication facilities as well as high performance computing (HPC) facilities at QUT. PhD2: Pore-network modelling of reactive transport As a PhD student, you will develop efficient pore-network modelling
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competitive scholarship. Eligibility Applications are invited for PhD Research Scholarships in the areas of Healthy Development: Disciplines include, but are not restricted to, allied health, biochemistry
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, and evaluation of advanced software engineering techniques and methodologies aimed at detecting, mitigating, and preventing misinformation online. The successful candidate will develop novel AI-driven
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algorithms and deep learning models. Have proficiency in Python in a Linux environment and development experience using Tensorflow or PyTorch. Have strong linear algebra and computer vision knowledge. Have
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and polyploid crop species and benchmark them against other methods such as graph-based methods. This project will combine algorithm development and computational programming with large population
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, programming, algorithms, and data analysis skills Outstanding research skills Applicants with Master degrees by research with technical publications and research experiences in structural dynamics and
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Nano SA Nano is a University of Adelaide spin-out company developing next generation microfluidic technologies for the synthesis of lipid nanoparticles (LNPs) and personalised mRNA medicines. Our mission
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solutions to problems they encounter, and positively develop safety risk intelligence (SRI). Key research questions include: What are the motivating conditions for developing safety risk intelligence in
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, addressing critical challenges in the transition to sustainable metallurgical processes. The successful candidate will develop a fundamental scientific framework to tackle key research questions in