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computer vision and machine learning methods to interpret the photovoltaic (PV) solar farm's condition and perform various inspections and anomaly detection. The research will draw from state-of-art
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quantitative methods. Expected outcomes include new knowledge on designing for technology-supported wellbeing, particularly when using human-centred AI. The project will involve critical analysis of existing
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the body. This project involves the development and application of advanced computer simulation methods to explore the mechanisms of ion conduction, selectivity and activation for ion channels that control
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) use computer vision/machine learning to quantity athlete performance. Develop new computer vision/machine learning methods to enable measurement of sports performance. Research program would make use
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The aim of this project is to describe ion conduction and activation/inactivation processes by employing molecular dynamics and statistical mechanical methods. The expected outcome is an improved
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The primary objective is the development of computational methods and experimental techniques to investigate failure modes and quantify defects and damage in fibre reinforced hybrid composites used
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the pioneers of methods based on ultrashort laser ablation in liquid ambient. These methods are now considered as the most efficient among laser-ablative pathways to finely control size and physico-chemical
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, structural variations, and evolutionary dynamics. In this project we will aim to develop novel dynamic programming computational methods for pangenome assembly of diploid and polyploid crop species and
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Applied mathematics, fluid mechanics, high-performance computer simulations. Two full time, fixed term positions (3 years) at Hawthorn campus $34,700 per annum (2025 rate) About the Scholarship
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tissues or reveal micro- or nano-structural features, like the small air sacs in lungs. To overcome these limitations, alternative X-ray imaging methods have been developed: X-ray phase-contrast and dark