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energy resources. The expected outcomes include technical advancement of distributed algorithms for managing energy resources at customer premises. The benefits include more resilient, secure, private, and
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The successful PhD candidate will undertake research in the following areas: Develop deep learning algorithms for autonomous robotic navigation using dual-view image fusion and shadow-based visual perception
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known as Team COMPAS -- includes a number of amazing undergraduate and graduate students, postdocs, alumni, and other fantastic collaborators. Please contact me if you are interested in joining our group
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cross-disciplinary and focussed on translating technological advances in biomedical engineering towards improving outcomes for cancer patients. PhD students within the group are supported by postdocs
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Christopher O'Neill ) Auditing Algorithms: Detecting and reducing discrimination in AI-Driven Decisions (Dr Charles Crabtree ) The changing nature of digital inequalities in an age of AI (Prof. Neil Selwyn
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explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group
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manufacturing through FDM, SLA, SLS printing technologies Expected outcomes The PhD project will generate novel numerical algorithms and design strategies, opening a new research avenue in computational
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behaviour, distribution, and management of perchlorate across Australia. Whilst primarily based at Flinders University, candidates will work collaboratively with the Energetic Materials Research Network
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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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determined by combining the observed space density of galaxies, the measured spatial distribution of galaxies and simulations of the dark matter distribution. Example themes for student projects follow and