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I supervise projects considering the evolution of accretion discs and their connection to observations. In particular, I consider discs that are warped or distorted (not flat). This geometry has been directly observed in planet forming discs around young stars (protoplanetary discs) and is...
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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
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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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or psychology with strong statistical training. You can check your eligibility with the PhD readiness tool . For full information on eligibility and English language requirements, please visit the Monash Business
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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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Current reseach is in the areas of: Development of biomimetic structures as ultrasound contrast agents Deep tissue imaging using photoacoustic contrast agents All optical photoacoustic sensors for tomagraphic imaging in tissue Neural network correction of distortions in acoustic transducers web...
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PhD Opportunity on Generative-AI driven Requirements Regulation in Space Missions Job No.: 687090 Location: Clayton campus Employment Type: Full-time Duration: The scholarship may be held for up
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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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PhD with full scholarship may also be offered a paid RA position to demonstrate their research potential and strengthen their publication record. Requirements: WAM > 80 Relevant research experience high
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PhD Scholarship in Generative Artificial Intelligence Job No.: 686325 Location: Clayton campus Employment Type: Full-time Duration: 3.5-year fixed-term appointment Remuneration: The successful