12 cyber-security-machine-learning PhD positions at Queensland University of Technology in Australia
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-time and/or external study is obtained). Road safety is an interdisciplinary area of research so a range of skills and experience will be considered, including: a background in public health, psychology
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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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. Through choreographed interactions with movement experts, this project expects to generate machine learning strategies to understand how people and robots can reliably and fluently move together. Expected
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degree in a full-time capacity prior to the application deadline (11:59pm AEST, 30 September, 2025) be studying a PhD in the area of road safety for children and/or active transport. If successful, you
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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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microfluidic fabrication and experiments 3D printing machine learning. Demonstrated programming skills (Matlab, C++, or Python). Desired Demonstrated ability to work independently and to formulate and tackle
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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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relevance to the research topic be applying to study full-time and at a QUT campus (internal study mode) start your research degree by the end of September 2025 not have secured an external sponsorship (e.g
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commercial lithium-ion batteries do not satisfy the increasing demands of portable electronic devices and electric vehicles, due to low energy densities, safety issues and high cost. High capacity electrode
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supported by an ARC Industry Fellowship, in partnership with Bush Heritage Australia. The student will work closely with ecologists and computer scientists at QUT and conservation managers at Bush Heritage