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About SecurEL SecurEL is a Centre for Environment-friendly Energy Research, facilitating a secure, resilient, and sustainable electricity distribution grid that ensures both the security of electricity
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objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as
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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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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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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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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
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and polyploid crop species and benchmark them against other methods such as graph-based methods. This project will combine algorithm development and computational programming with large population
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algorithms are used that allow a computer to process large data-sets and learn patterns and behaviours, thus allowing them to respond when the same patterns are seen in new data. This include 'supervised
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of distributed MIMO, and/or coordinated multi-AP operation (under study in the Wi-Fi 8 standardisation workgroup), using Hardware Description Language on FPGA, based on the open-source openwifi project (https
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and