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/C++) computer codes implementing a cryptographic algorithm. Although desired, background in advanced cryptography is not a must. Application of a PET algorithm to solve a real-life problem: This
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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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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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Strait Islander peoples. This ground-breaking course is a transformational leadership program for Indigenous Australians, designed to strengthen Australia’s Indigenous workforce in public, private and
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. Guaranteed place in the IT IBL program . Number offered Two scholarships available. Selection criteria Awarded based on need. To retain this scholarship: You must maintain a Weighted Average Mark (WAM) of 50
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for a place in Monash Minds, a full-funded leadership program for Indigenous first-year students. Number offered One scholarship available. Selection criteria Awarded based on need. To retain
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value $21,500 Number offered Varies (Depend on funding) See details Bachelor of Computer Science Moksh Receiving a scholarship has been my motivation to study harder. It has also given me more confidence
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scholarship, I have been able to purchase a new computer to assist in my studies. This improved my capacity to focus on my studies and achieve my academic goals. Law has been a dream of mine for a long time
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wouldn't be possible. Am I eligible? You must be one of the following: An Australian citizen You must meet the following criteria: Commencing full-time studies in a Monash Enabling program/Monash Transition
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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...