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trading decisions under high price volatility. This PhD position focuses on designing, developing, and evaluating self-learning energy trading algorithms that are able to cope with these challenges. By
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reference architecture for data visiting. This paradigm enables algorithms to securely access and process data within the environments where it resides, supporting federated learning for training machine
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wing panels. Reliable process control is critical: underheating leads to poor bonding, while overheating causes polymer degradation. At the heart of process control algorithms lies a physics-based
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scheduled in the period 13 till 17 October 2025 and interviews can be held through Microsoft Teams. A second round of in-person interviews may be scheduled (in de first week of November) if necessary. A