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planning and decision-making. Working with real-world data from Alliander, you will publish at leading machine learning venues while building tools with tangible impact on the Dutch energy sector. The Dutch
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decision-making. Working with real-world data from Alliander, you will publish at leading machine learning venues while building tools with tangible impact on the Dutch energy sector. The Dutch energy
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Are you fascinated by how machine learning can enhance control without compromising safety or stability? As a PhD candidate, you will develop scalable methods for expressive and flexible neural
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decision-making. Working with real-world data from Alliander, you will publish at leading machine learning venues while building tools with tangible impact on the Dutch energy sector. The Dutch energy
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Job description We invite applications for a fully funded PhD position in the area of Scientific Machine Learning (SciML), which integrates data-driven machine learning techniques with established
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communication systems, we encourage you to apply—even if you do not meet every item in the project description. We value candidates who are eager to learn, think creatively, and work across disciplinary
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reinforcement learning to derive provable guarantees on resilience. You will work at the interface of these two highly timely perspectives, contributing to both the algorithmic development and the formal analysis
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reinforcement to uphold the highest safety standards. A major risk to dike stability is Backward Erosion Piping (BEP): groundwater flow underneath a dike entrains sand particles, eroding the base of the dike
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); an affinity for one or more of: world models, generative modelling, causal/representation learning, reinforcement or imitation learning, dynamical systems, or robotics; the ability to formulate and pursue
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components. You will explore how learning-based methods, such as imitation learning and reinforcement learning, can be integrated with model-based low-level controllers and multimodal sensing to enable contact