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On this page Contact details Enquiries Search staff by name Campus locations and maps Transport and facilities Contact and Maps Only a short walk or tram ride from Melbourne's city centre, the University of Melbourne’s main Parkville campus is a well-known city landmark, with unique cultural,...
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Respect at Melbourne Content warning: This website includes information on sexual harassment and sexual assault and may be distressing for some people. For support, contact the Safer Community
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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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events with the GOTO telescope network. Projects focussing on thermonuclear bursts will involve analysis of new and archival data from satellite-based X-ray telescopes, and running numerical models
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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Status: Closed Applications open: 18/05/2025 Applications close: 9/06/2025 View printable version [.pdf] About this scholarship Description/Applicant information A PhD scholarship in
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Cabrini/Monash Nursing and Midwifery PhD Scholarship Program – The Peter Meese Cabrini Oncology Nursing PhD Scholarship Job No.: 690199 Location: To be confirmed (Clayton/Malvern) Employment Type
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, which are some of the most numerous stars in the Universe. "Weighing stars using stellar vibrations: Asteroseismic masses of Red Giant Stars using space telescope data" "Using optical telescope
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! Possible projects involve massive stellar binaries, gravitational-wave data analysis, astrostatistics, dynamics in galactic centres and globular clusters, probes of general relativity in the strong-field
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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