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Field
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key part in supporting Australia’s transition to green ironmaking by developing a quantitative framework that connects impurity content, process parameters and microstructural evolution to scalable, low
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for enhanced durability, performing microstructural analysis and mechanical testing. Topology Optimization & AI Integration: Use AI and machine learning to guide structural and topology optimization, creating
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valorisation, degradation kinetics & durability, mineralogical phase characterisation of materials, lab-based testing on electrochemical techniques, microstructure performance evaluation and computational
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cladding processes, including parameter optimisation and advanced monitoring techniques. Develop and refine process models, simulations, and automation strategies. Characterise microstructure, wear behaviour
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methods for characterizing hydrophobic and anti-icing properties based on ice adhesion testing, profilometry, and ice wind tunnel testing; Experience in characterizing the microstructure and performance
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faced by the oil and gas industry, where the knowledge of correlation between microstructural and mechanical properties of polymer composites after aging is very limited. The project will be organized
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processing, specimen preparation, microstructural and chemical characterization, and electrochemical performance evaluation. Depending on background and interests, the work may also involve exploring bio
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Science, develops methods and quantitative approaches to investigate nano- and microstructural features across soft matter, biological tissues, as well as metals and alloys. Our work combines X-ray and
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data-driven approach to microstructure imaging” (ADAMI), funded by the European Union. ADAMI is a highly interdisciplinary project that combines insights from physics/engineering (MRI and light-sheet
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wide range of tasks in the field of magnetic material preparation and characterization. This preferentially includes the independent characterization of the magnetic microstructure through the combined