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Job Description If you are passionate about advancing the frontiers of process mining and data-driven intelligence, and you want to build your career in one of the fastest-growing research areas
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systems for both learning and dynamical systems. This work will include new approaches to online learning of optimal policies for hierarchical cyber-physical systems, mixing components of learning and
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is vital to the security of our society. We teach and conduct research in cyber security, information security, communications networks and networked services. Our areas of expertise include biometrics
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of electrical systems and system analysis to find possibilities for electrification and decarbonization diagnostics and monitoring of equipment and systems cyber security, 5G data communications, and artificial
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16 Sep 2025 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Computer science » Cybernetics Computer science » Programming Researcher Profile First Stage
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2 Oct 2025 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Engineering » Process engineering Engineering » Simulation engineering Researcher Profile
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their root cause. This builds on the works of the cyber analytics lab (www.cyber-analytics.nl) and CISElab (www.ciselab.nl) at TU Delft. The project is a close collaboration between the labs at TU Delft, where
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-based modelling, quantitative resilience assessment, and risk analysis to simulate and optimise resilience strategies. The framework will be tested and refined through pilot studies in collaboration with
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and the Department for Transport. The aim of this PhD project is to develop a unified approach for risk analysis of cyber-physical transport systems. Essential transportation services are increasingly
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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