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including number theory, dynamical systems, probability theory, equidistribution theory and optimal transport. The aim of the PhD project is to develop a flexible framework based on harmonic analysis to study
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available here . Key Accountabilities Research Assistant / Research Associate Support development and documentation of Python-based Design Tool workflow for D-Suite Project Formulate and solve optimization
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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; implementation of digital twins that enable real-time decision optimization; and establishment of cross-industry frameworks that allow technology transfer between sectors. Your findings will be published in high
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. The research group is seeking a talented Doctoral Researcher in nonlinear systems and control with strong interest in nonlinear stability theory, modeling & identification, optimal control, certifiably safe
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. The project focuses on power-aware computing, thermal optimization, and sustainable electronic design, targeting critical applications in aerospace, healthcare, and industrial automation. Hosted by the renowned
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, scalability, and adaptability to various applications such as autonomous systems, IoT devices, and wearable technologies. Research Focus Areas: 1- Neuromorphic and AI-Optimized Processors: Design AI-specific
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safety questions: Determining optimal stored energy requirements for grid support, considering various timescales and power ratings. Reviewing and benchmarking storage technologies (lithium-ion batteries
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, determining optimal ways for groups of buildings to share resources and benefits. You will investigate and quantify trade-offs between individual objectives and collective outcomes, focusing on scalability
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process. Address blind inverse problems by defining a network to learn distortion functions from data, informing the optimization in the learning process. Refine optimization and learning strategies