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to trick AI-based models, pay little attention to fake-normal data traffic generated by Generative Adversarial Networks (GAN). This PhD research will address a major vulnerability in AI based smart grids by
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achievements, list of publications, work history and references A copy of your academic transcript(s) At least one referee report with signature Enquiries Associate Professor Peter Poon, Director, Supportive and
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degree . In your EOI, nominate Associate Professor Angela Watson as your proposed principal supervisor, and copy the link to this scholarship website into question two of the financial details section
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understanding of gene presence/absence, structural variations, and evolutionary dynamics. In this project we will aim to develop novel dynamic programming computational methods for pangenome assembly of diploid
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interested in connecting spatial and spectral information to understand complex materials systems at the molecular level with machine learning. PhD Student A will work with tumour sections to develop multiple
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, nominate Dr Andrew Stephens as your proposed principal supervisor, and copy the link to this scholarship web page into question two of the financial details section. About the scholarship This PhD project
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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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manufacturing sectors into valuable products. The scholarship will support one student to work on the development of novel biomass based adsorbents for CO2 capture. A combined experimental and simulation methods
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degree . In your EOI, nominate Dr Mahboobeh Shahbazi as your proposed principal supervisor, and copy the link to this scholarship website into Question 2 of the Financial details section. About the
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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