31 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"J.-F" PhD positions at Monash University
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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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, to trace the chemical enrichment of the universe, and even to better understand planet formation. Most of my research involves huge data sets with observations of all different kinds (e.g., photometry
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projects that involve data analysis, the application of artificial intelligence, the development of new detection techniques, and the exploration of new experimental methods through collaboration with our
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Understanding factors related to student retention and experience in physics and astrophysics major units. Using quantitative (surveys) and qualitative data (interviews with students) this project
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will have the opportunity to interact with gravitational-wave researchers throughout Australia and around the world. Students in my group use data from the Laser Interferometer Gravitational-wave
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combination of multi-wavelength observational data with sophisticated simulations. I am a member of various collaborations, including Australia's OzGrav Centre of Excellence for Gravitational-wave Discovery
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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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disability, and contributes directly to nationally significant health and disability policy reforms. The successful candidate will undertake data-driven, policy-relevant research using advanced quantitative
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recently been awarded an Incorporating Patient Data in Health Technology Decision Making Grant under the 2025 Preventative and Public Health Research Initiative of the Medical Research Future Fund (MRFF
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shape health, employment, and wellbeing outcomes for individuals and families. The successful candidate will join a highly collaborative research team using linked employer–employee administrative data