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to support effective mitigation of cyber-threats. Indeed, AI is revolutionizing the field of cybersecurity, for instance by enabling faster and more efficient responses to evolving threats. However, despite
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therefore focus on a key challenge in this domain: the design of next generation decision support tools for battery operators, focusing on the participation in multiple consecutive short-term electricity
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sensors, communicating over networks, to achieve complex functionalities, at both slow and fast timeframes, and at different safety criticalities. Future connectivity of the next generation of multiple
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on the participation in multiple consecutive short-term electricity markets and congestion management. To address this question, you will develop state-of-the-art model predictive control tools to guide market
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decision-support or safety-critical systems. Knowledge of Cyber-Physical Systems, Sensor Fusion, or Risk Management is an advantage. Excellent programming skills (Python, C++, or similar). Ability to work in
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extended from cloud solutions (such as OpenLLMetry), the research question is how to identify anomalies in collected information that can come from multiple AI services either invoked manually by users or by
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/research-groups/CRITIX/ ) headed by Prof. Marcus Völp. The team focuses on critical information infrastructures and cyber-physical systems with the aim to protect our most sensitive and valuable assets. We
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focuses on critical information infrastructures and cyber-physical systems with the aim to protect our most sensitive and valuable assets. We look into systems in the small and how we can prepare them