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www.qut.edu.au Verifying you are human. This may take a few seconds. www.qut.edu.au needs to review the security of your connection before proceeding. Verification is taking longer than expected. Check your Internet connection and refresh the page if the issue persists. Verification...
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the ARC Research Hub for Value-Added Processing of Underutilised Carbon Waste, which is established in 2024 with the aim for developing advance upcycling technologies and associated regulatory and social
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UniSA will have merged to create a brand-new institution, Adelaide University. In the lead up to this historic event, the Scholarship application process will be affected. Application Process Scholarship
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, applicants must: Be enrolled in your first year of a PhD program at the University of Newcastle, conducting research related to alternative energy resources. Application Procedure As part of the application
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/ . Applicants with either Master or Bachelor degrees with scientific publications and research experiences in chemistry, materials science, electronic devices or related fields are preferred. Application process
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conversion of biomass into high-value platform chemicals and bio-slurry fuels. The project builds on our patented and published bench-scale work, aiming to scale up the process to continuous operation using
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Graphs/ AI methods to this domain. This position has a two-stage selection process: Stage 1: Please submit an EOI using the Faculty of Information Technology Research Project Enquiry form here
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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
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external organisations. Applicants from a range of disciplines or fields will be considered, including electrical, electronics, computer systems or telecommunications engineering. If you're curious about
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/Computer Engineering, Computer Science, Applied Maths or related. Strong skills in AI techniques/ML/optimisation (Python/Matlab); familiarity with probabilistic modelling, time-series or control/power