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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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different from when core theories about the role of media in society were established. We are awash in data about clicks, views, and likes, but we lack evidence about what people now do with media, how
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project supported by an ERC Advanced Grant on the Theory of Materials for Bioelectronics. The overall goal of our research is to describe a class of organic materials able to transport ionic and electronic
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affect surface outcomes, benchmark against conventional techniques, and evaluate performance of the finished components. You’ll also delve into intelligent automation and machine learning to optimise
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factors involved in the onset and progression of dementia. Advanced computational methods, including bioinformatics pipelines and machine learning, will be employed to uncover putative biomarkers and
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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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dementia may be exacerbated by cognitive decline, loss of memory, learning disabilities, attention deficits, and motor skills deterioration, which result in reduced ability of the care workers to perform
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candidate willing to learn new skills and undertake statistical analyses using a variety of datasets. People within Australia with a relevant Honours or Masters (e.g Public Health, Biostatistics, Epidemiology
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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deep learning. The purpose of this scholarship is to support a PhD student to contribute to the advancement of infrastructure monitoring technologies with strong industry collaboration. Student type