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focused on the development and application of recycled and waste-derived materials for advanced engineering systems. The role will emphasise computational modelling, simulation, and data-driven approaches
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people who discover them The Opportunity Join an ARC-funded research project developing numerical methods to simulate the flow of dense viscous liquids through a deformable granular mush. The project aims
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focused on the design and development of advanced power electronic systems. The primary role will involve the design, simulation, and validation of power electronics, including converter design
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: emerging mobility, mixed traffic modelling, connected and automated vehicles, micromobility, experimental design using driving simulators, virtual reality (VR) and augmented virtual testing, and test tracks
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underwater vehicles. We will explore advanced non-parametric mapping techniques based on our prior work in the area of Gaussian Process based Simultaneous Localisation and Mapping (SLAM) and recent advances
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combined with first principles and multiscale simulation for the design of molecules, catalysts and materials, with applications in clean energy and decarbonisation AI for clinical and health research using
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area of Gaussian Process based Simultaneous Localisation and Mapping (SLAM) and recent advances in non-parametric, 3D environment modelling. We will assess the utility of these tools for map-building
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-performance computing and geochemical modelling to decipher atmospheric CO2 removal mechanisms over geological timescales. The research involves integrating surface process simulations with tectonic frameworks
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and perform numerical simulations To be successful at Level B please address the selection criteria A PhD or equivalent in data science, social network analysis, mathematical modelling, statistics
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with experience. • Demonstrated research experience in Modelling and Simulation (M&S) and decision support analytics, stakeholder engagement and an active research agenda evidenced by research, supported