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Our industry partners are developing software for automation of Hydrogen Deuterium Mass Spectrometry, which can connect structure, behaviour and function of proteins, for understanding diseases and
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Skip to main content Main Menu - Primary Home Projects Supervisors Expression of Interest Contact Immersive Visualization of Protein Structures in Food Science Using VR/AR Primary supervisor Wai Peng
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biological networks as a form of relational and structural learning. Given a network dataset, we wish to infer a model of the distribution of the elements of this data-set, possibly as a mixture of several
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to uncover the role of structure in the glass transition and how the disordered structure of a glass gives rise to unique glass behaviour such as ageing and brittle mechanical failure. Unlike crystals which
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group’s projects often combine astronomy, coding, visualisation, and data science, and work well for students who enjoy either astrophysics, machine learning/coding, or both. The multidimensional structure
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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
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in conventional imaging, and to access a complementary ‘dark-field’ signal that originates from tiny sample structures. We do this by designing and implementing novel experimental set-ups and
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I am an ARC Future (former DECRA) Fellow and lead the Structured Nanophotonics Group at Monash University. My research in nanophotonics explores the full potential and multi-dimensional nature
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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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discovery. While deep generative models have shown promise in proposing novel molecular structures, they typically require massive, cleanly labelled datasets to train effectively. In practice, acquiring high