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Social Science PhD Opportunity on Home Helper Robots Job No.: 678806 Location: Caulfield campus Employment Type: Full-time Duration: The scholarship may be held for up to 3.5 years (fulltime
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mathematical integration, with the desired outcome being to increase the water and/or nitrogen use efficiency of Australian cropping systems. We propose to use a range of emerging data science approaches within
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, to inform clinical practice and policy. Understanding the basic visual and higher visuo-perceptual profiles of children with cerebral palsy will also contribute to scientific and theoretical knowledge
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of learnt features in deep neural networks. Specifically, we aim to: • Develop methodologies to interpret and visualize the features learnt by neural networks in a human-understandable manner. • Investigate
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detection and visualization, physics modelling and vibration characteristic identification techniques will be included in the digital twin frameworks. AI techniques will be further developed for simulating
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graduate research options in engineering. Business and economics Discover your graduate research options in business and economics. Science Discover your graduate research options in science. Education
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synchrotron technology. The candidate should have experience in one or more of the following research areas: Chemical Engineering, Chemistry, Chemical Sensing, Environmental Science, Mineral Processing