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Roentgen’s Nobel Prize-winning discovery of X-rays enabled us to non-destructively image inside the body, birthing medical diagnostic imaging and revolutionising materials characterisation. Absorption of X-rays in an object provides conventional X-ray image contrast, but absorption of this...
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with leading experts in the field. Applicants should have a strong background in machine learning, graph-based methods, and an interest in causal learning. Scholarships are awarded based on academic
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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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PhD Scholarship in Digital Mapping of Homemade & DIY Cultural Economies in First Nations Communities
PhD Scholarship in Digital Mapping of Homemade & DIY Cultural Economies in First Nations Communities Job No.: 681214 Location: Clayton campus Employment Type: Full-time Duration: 3.5-year fixed-term
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Application dates Applications close30 June 2025 What you'll receive You'll receive a stipend of $33,637 per annum for a maximum duration of 3.5 years while undertaking a QUT PhD. The duration
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forward for a School-funded scholarship. Expertise in Human-Computer Interaction and Human-Centred Computing. Interest in Human-Centred AI and Social Computing. Aspiration to publish in leading venues
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-based molecular biophysics project of medical significance, funded by the National Institutes of Health, USA. The Computational Biophysics Group develops advanced physical and chemical simulation
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models through specific activation functions. This project will be undertaken in collaboration with Dr Hemanth Saratchandran and Prof Simon Lucey of the Australian Institute for Machine Learning, and
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surveillance activities and minimise the global burden of acute respiratory infection. This PhD project will use data from FluTracking to evaluate ILI duration among different populations groups, factors
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The successful applicant will conduct research to design and develop novel machine/deep learning based trust technologies for securing IoT services/devices. The successful applicant will conduct