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Stochastic Analysis, (4) Discrete and Geometric Analysis, (5) Statistics and Data Science, and (6) Partial Differential Equations and Modelling. The Department of Mathematics (DMATH), headed by Prof. Dr
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emphasis is given to numerical simulation to reduce the required experimental effort, but the validation of the models on laboratory setup will remain an essential asset. The Department of Engineering (DoE
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process thanks to the use of Deep-Reinforcement Learning (DRL) to orchestrate the joint use of multiple attack surface tools, Large-Language Models (LLMs) to refine their configurations and graph-based
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experience of the trainee which is essential to ensure continuous education and learning. In this project SnT will lead activities to define and develop AI models to be used when creating scenario contents
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implementation of data governance, security, and compliance policies Document data models, workflows, and technical architecture Monitor data flows and troubleshoot issues in production environments Contribute
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cybersecurity allowing thus to validate and receive feedback from on-the-field cybersecurity practitioners. As generative AI (GenAI) platforms and large language models (LLMs) are increasingly integrated
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the impacts of various anonymization techniques from a business, legal and regulatory standpoint Designing and evaluating a reference process model to guide the implementation of legally compliant data
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consolidated data model and advanced analytics to facilitate strategic decisions with relevant stakeholders. The candidate will be involved in various (inter-)national initiatives and engaged with different
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understanding, to address challenges in dynamical systems and engineering flows and enable first-principles modeling. This involves: Developing machine learning methods that fuse nonlinear dimensionality
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in a number of the following topics: Turbulence modeling with wave propagation simulations Modulations used in optical wireless communications Data Analysis and Management Implement and open-source