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gas is a crucial aspect of the ongoing energy transition, serving as a renewable energy source for industrial processes and a substitute for fossil fuels. Australia, with abundant and cost-effective
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. Your project will explore Stream Finishing, a cutting-edge surface engineering technology that offers unmatched precision and control over traditional methods. You’ll investigate how process parameters
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storage and greenhouse gas upgrading at reduced operation temperatures featuring high efficiency, selectivity, superior stability, and cost effectiveness. This project should provide significant benefits
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and hands-on experience with AI and computer vision. Solid programming skills in Python, especially with PyTorch. Practical experience with deep learning projects, including working with attention
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of young people and people who work in, visit or oversee police custody and to examine the frameworks, policies, processes and resources available to guide and support the management and care of young people
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involves a competitive process, with shortlisted applicants notified of outcomes by November 2024. Scholarship Details Maximum number awarded 1 Eligible courses All applicable HDR courses. Eligibility
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of generative AI. Essential Skills and Experience A background in a relevant field such as behavioural science, cognitive science, data science, psychology, human-computer interaction, law, or a related
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process. Closing date 15 February 2026 Further information Further information about this scholarship can be obtained by emailing Janet Wade at hdrinternational@unisq.edu.au . This partnership between UniSQ
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modelling of atomic collision processes. Student type Future Students Faculties and centres Faculty of Science & Engineering Science courses Course type Higher Degree by Research Citizenship Australian
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on mechanical and physical separation methods for efficient recovery of active materials and components from spent LFP cells as well as development of hydrothermal relithiation processes to restore