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Field
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) and the University of California Irvine (UCI). The Research School "Foundations of AI" focuses on advancing AI methods, including energy-efficient and privacy-aware algorithms, fair and explainable
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modelling and simulation of transmission and distribution networks, including benchmarking data models, developing optimal power flow algorithms, and creating state estimation and multi-energy optimisation
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, tailored, complex materials such as advanced polymers or polymeric formulations, catalysts, mechatronic devices and software and algorithms. Design, control and modelling and analyses complement
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novel opportunity to automate and improve the frailty assessment process, aiming for greater consistency and predictive accuracy. Aims i) Develop a deep learning algorithm to autonomously detect and
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analytics, anomaly detection, and embedded redundancy to enhance system resilience. Students will focus on creating adaptive algorithms and hardware implementations that enable real-time diagnostics and
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will design quantum-safe threshold encryption and/or authentication algorithms. The expected outcome is the design of methods, techniques and their software prototype to implement quantum-safe threshold
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CST Microwave Studio, HFSS or EM Pro for antenna modeling and design is required, as is experience with programming languages like MATLAB, Python, or similar for antenna array analysis and algorithm
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of topics include algorithmic fairness in network analysis, developing network embedding frameworks for real-world network datasets or AI models based on agentic LLMs for simulating real-world network data
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of software interfaces and data models Selection and configuration of algorithms for annotating and organizing research data and software using state-of-the-art AI technologies Ensuring the sustainability and
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of superconducting qubits to quantify performance and identify limiting physical mechanisms Perform quantum device calibrations, benchmarking, and run quantum algorithms Presenting and publishing the research