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implementation partners to improve care through digital technology and develop a sustainable service model for future sleep coaching program delivery. Monash School of Psychological Sciences, ARC Industrial
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these methods to understand the atomic structure and properties of a range of materials being developed for efficient solar cells, light generation, batteries, superconductors, photonics and nanoelectronics. We
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the research outcomes, skilled workforce, technology and partnerships to improve human health locally and globally. Supervisory team The project will be co-supervised by Associate Professor Shalini Arunogiri
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violence, technology and crime, policing, and crime prevention. Monash Criminology is distinct in Australia for its consistent success in attracting national and international competitive funding for major
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theoretical colleagues. All research takes place within our dynamic particle physics research group with academics and postdocs, as well as graduate and undergraduate students. Some work will be purely
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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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I supervise a wide range of PhD projects on experimental research into the electronic properties of novel quantum materials including topological insulators, graphene, and other atomically thin two-dimensional materials. I am interested in creating a low-power topological transistor, in which an...
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organic nanomaterials for future electronics, optoelectronics and spintronics" "Light-transformed materials" "Theoretical and numerical modelling of the electronic structure of functional low-dimensional
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in conventional imaging, and to access a complementary ‘dark-field’ signal that originates from tiny sample structures. We do this by designing and implementing novel experimental set-ups and
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they bond in materials, but also develop transferable skills in scientific computing, data analysis and visualisation. "Machine learning for atomic-scale structure determination in thick nanostructures" (with