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large international consortium. Within the project you will work with different types of water, ranging from surface water to wastewater treatment plant effluent. The work will integrate hands
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tailored surveys for enriching the understanding of the mixed system. The behavioural understanding on the demand side will provide information to the supply side, such as the trade-offs between different
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research areas encompass the synthesis of novel converter topologies, development of specialized control and protection algorithms, integration of cutting-edge components, and formulation of design
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electrical power, enabling smart sensors to operate without batteries. You will explore novel capacitor-based rectifier architectures, adaptive impedance-matching algorithms, and on-chip protection mechanisms
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mathematical methods, algorithms, and applications are required. Simulators are a recognized method for architectural design explorations and the implementation of software development platforms. The goal
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machine learning. The position will involve working with different research groups in the Department of Computer Science at the University of Cambridge, UK. In this collaborative project, we will apply
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specifically naval architecture, generative AI is lagging behind. This is largely due to data scarcity in the maritime domain. Unlike media domains where vast datasets are readily available, ship design data is
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specifically naval architecture, generative AI is lagging behind. This is largely due to data scarcity in the maritime domain. Unlike media domains where vast datasets are readily available, ship design data is
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supervisors, from different universities: Dr. Georgios Tsaousoglou at DTU, and Dr. Maryam Kamgarpour at EPFL, Lausanne, Switzerland, with the opportunity to undertake an extended research stay at EPFL. Project
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analysis, AI algorithm modeling, testing, and integration into functional systems within the project scope. Specifically, in activities related to behavior modeling from IoT device data, generative AI