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. The candidate will work closely with the CIs, post doc and PhD (machine learning) candidate, to develop choreographic structures used to generate movement and interaction capabilities that will define human-robot
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) use computer vision/machine learning to quantity athlete performance. Develop new computer vision/machine learning methods to enable measurement of sports performance. Research program would make use
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courses. Browse all courses Take your development further with advanced learning and award pathways. Pathways to Politics for Women Public Sector Management Enterprise Leadership For organisations Achieve
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, the student will have the opportunity to contribute to the development of novel biocontrol tools for the control of medically important mosquitoes in Australia. The project will suit candidates with interests
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-year research project on generative AI and academic research develop a research proposal that responds to and aligns with the scholarship topic and articulates the contribution your research will make
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effort, or the amount of information a player takes on board before making a decision is challenging. Can we develop AI solutions to track off-ball effort? Can we monitor how players scan the field? Can we
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focuses on developing the first-ever closed-loop cardiopulmonary resuscitation (CPR) feedback device. The device uses non-invasive sensors to measure blood oxygenation in the brain and tells the CPR
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will help to inform the development of effective, targeted countermeasures as well as assist with identifying potentially opportune times for early intervention. There is a need to expand the current
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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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Foundation Program including specialist training and development, and the opportunity to undertake a 12-month industry placement. Eligibility You need to meet the entry requirements for QUT's Doctor