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. This project seeks to advance energy autonomy by optimising power conversion, storage, and distribution in such systems, enabling broader adoption in real-world applications. The project aims to develop a PMC
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optimisation algorithms to dynamically reconfigure the substation/distribution network settings to enhance the system efficiency. The optimisation algorithms will incorporate the uncertainties associated with
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of nanofabricated sample supports and tracking algorithms for 5D electron diffraction (5DED). EMAT is one of the leading electron microscopy centers in the world and has a vast expertise in both fundamental and
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PhD Stipends within Distributed, Embedded and Intelligent Systems (DEIS) At the Technical Faculty of IT and Design, Department of Computer Science, one PhD stipend is available within
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achieve automated data driven optimization (in terms of time and quality) of polishing process parameters by application of machine learning algorithms, leading to a robust, repeatable and fast polishing
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as to what role law should play in reducing potential harms, in helping to distribute risks and benefits across different groups in society, and in how existing (or future) legal rights and duties
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in Adelaide and Melbourne. Expected outcomes The Finite Element Method (FEM) is the current dominant approach for modelling real-world signals but requires substantial, uniformly distributed data. Real
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better and faster decisions when assessing funding applications, ensuring the efficient and unbiased elimination of poor applications? This question can be addressed through training algorithms on past
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the distribution of mechanical loads in the wind farm, thus also extending the lifetime of the wind farm. Your PhD project is integrated into the Living Lab 70 GW Offshore Wind, which researches crucial aspects
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and application architectures with implementations of massively distributed embedded systems that interact with each other and their environment to enable secure, goal-driven, autonomous and evolvable