47 data-"https:" "https:" "https:" "https:" "https:" "RMIT University" PhD positions at Monash University in Australia
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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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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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, 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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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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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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explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group
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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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electromagnetic signatures, primarily focussed on linking the data from these exciting experiments with our theoretical understanding of gravity and the most extreme regions of the Universe. I am a member of the
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are supported by quantum mechanical theoretical formalisms. Our fundamental findings yield promise for future applications in electronics, optoelectronics, spintronics, information processing and storage, sensing
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measurements in particle physics. Many of my projects are informed directly by current measurements, e.g. addressing new or unexpected features seen in the data. Others focus on improving the formal accuracy