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interconnected nature of these systems demand advanced modeling and control tools that leverage their distributed and structured characteristics for effective optimization and performance. Information As an
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, enabling engineers to predict and optimize system behavior across electrical, magnetic, mechanical, and thermal domains. Technologies such as multi-degree-of-freedom systems (e.g., maglev planar motors
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offers transformative potential in this space, enabling automation of complex tasks, optimization of design flows, and adaptive systems. Techniques like reinforcement learning, neural architecture search
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networks also need to evolve, offering, e.g., ubiquitous connectivity and decentralised data-center capabilities to optimize urban performance. This project aims to explore how telecommunications networks
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system performance and guiding the design process. 2. System Optimization for Cost and Performance: Using your numerical model, you will conduct extensive optimization studies. The goal is to fine-tune
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. The PhD candidate will combine materials science, computational modelling to design a novel framework that identifies optimal materials and AM processes based on performance, sustainability, and reusability
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quantum chemistry to logistics, energy systems, and AI-driven optimization. These problems are widely regarded as the natural domain of quantum computers, yet they remain extremely demanding for both
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Consolidator Grant, THERMODON on harnessing the unique capabilities of ONNs to solve combinatorial optimization problems. ONNs, inspired by the dynamics of coupled oscillators, exhibit inherent properties
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, patient motion, and more. Today, these parameters are either manually configured, heuristically optimized, or compensated post hoc using multi-level calibration scans or corrections, which introduces
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. Based on these insights, you will formulate design rules to predict optimal loading conditions and release mechanisms, supporting experimental optimization. We expect you to be able to work with a high