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computers to large-scale multi-dimensional simulations on high-end supercomputers, depending on your interests and inclinations. "Modelling extreme supernova explosions: From fast and faint to bright and
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recognition Individual and group behaviour understanding Long-term behaviour prediction Multi-task learning and foundation models Zero-shot and open-set recognition Privacy-preserving AI using anonymised human
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-field imaging of dynamic processes" "Multi-scale X-ray speckle-based imaging" "Spectral X-ray speckle-based imaging" "Single-shot multi-projection X-ray phase-contrast imaging" "X-ray virtual histology
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My research focusses on understanding stars: their evolution and chemical composition, and how they move throughout our galaxy. Most of what we know about the universe comes from starlight, but
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sexism, violence-supportive attitudes and coordinated harassment at scale? How can benchmark datasets be constructed to support robust and explainable AI models for online safety research? How do
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datasets with different configurations (e.g., number of channels, sampling frequency and resolution). To leverage large-scale self-supervised learning to train models on unlabeled EEG data, reducing reliance
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, laboratory, coding or prototype-development experience. Academic transcripts, including GPA/WAM and an explanation of the grading scale. Evidence of English-language proficiency, where applicable. Contact
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The goal of my research is to synthesise and characterise functional low-dimensional materials with atomic-scale precision and tailored electronic, optoelectronic, magnetic and chemical properties
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they bond in materials, but also develop transferable skills in scientific computing, data analysis and visualisation. "Machine learning for atomic-scale structure determination in thick nanostructures" (with
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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