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affected by rare genetic disorders. Key Responsibilities: Conduct independent research or as part of a team on projects related to stem cells, cardiogenesis, and cardiovascular biology Contribute
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their potential at Monash University. The scholarship program amplifies diversity in STEM through empowering scholarship recipients to achieve academic success. Total scholarship value $6000 Number offered 10 See
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My area of expertise is condensed matter theory. I am interested in the interplay between interactions and unconventional electronic properties of novel materials including graphene, topological insulators and Weyl semimetals. The former favours quantum states of matter (e.g. excitonic...
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My interests span a wide range of topics in theoretical physics, including: geometric phases, topological defects in matter and radiation fields, inverse problems (scalar and vector tomography), singular optics, using electrons, atoms and light and the exploration of complex systems using...
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We live and work in a world of complex relationships between data, systems, knowledge, people, documents, biology, software, society, politics, commerce and so on. We can model these relationships
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the environment and drives innovation. This role is focused on growing philanthropic support across several of Monash’s world-leading faculties, including science, engineering and information technology. You don’t
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, with an operational footprint globally, the Maintenance Technology Institute (MTI) is a commercially orientated, professional research and engineering organisation that has been providing professional
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for Earth" grant by Microsoft, one of only 6 projects in Australia to receive this recognition. The new project will build original frameworks for future applications of Machine Learning and Computer Vision
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& Infrastructure Coordinator The Opportunity Join a dynamic academic community as the Senior Resource & Infrastructure Coordinator in the School of Psychological Sciences. This key role supports research programs by
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The world is dynamic, in constant flux. However, machine learning typically learns static models from historical data. As the world changes, these models decline in performance, sometimes catastrophically so. This PhD will develop technologies for addressing this serious problem, building upon...