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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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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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determined by combining the observed space density of galaxies, the measured spatial distribution of galaxies and simulations of the dark matter distribution. Example themes for student projects follow and
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of masculinity, especially in relation to younger male audiences. The successful applicant may explore such questions as: What drives engagement with manosphere communities? How do algorithmic systems and platform
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Focus The PhD candidate will undertake research including: Experimental characterisation of aerosol generation, plume structure, droplet-size distribution, velocity fields and entrainment in a jet
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federated learning and multimodal deep learning models for healthcare. The project will focus on enabling privacy-preserving learning from distributed healthcare data sources, including longitudinal medical
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, segmentation, anomaly detection and learning in the context of non-stationary distributions. The candidate will also be connected to the Faculty of Information Technology. The Temporal Analytics Lab, directed by
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formed? Why does the velocity distribution of hypervelocity stars ejected from the Galactic centre not match expectations? How are the birth masses and natal kicks of neutron stars and black holes
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distribution functions. Total content of H2 in the solar neighbourhood and nearby galaxies and how they compare to other gas/dust tracers. Extinction mapping from resolved stars in nearby galaxies. Studying mass