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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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, as well as satellite and sensor data, looking specifically at 6 different use cases across Europe. In addition to the detailed innovative analysis of existing methods and protocols, ITC will focus
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strive to broaden our research portfolio! The challenge There is huge potential to benefit from the increasing availability of (big) data in the transportation domain. A wide range of sensors, part of
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, medical devices, or soft-tissue phantoms is highly valued. Familiarity with system integration, sensor technologies, or imaging modalities (e.g., X-ray fluoroscopy, endoscopy) is considered a strong asset
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deep learning algorithms. We welcome applications from individuals with experience in: Experience developing deep learning models for real-time image/video segmentation, object tracking, reinforcement
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algorithms that maximize the information extracted from images and delivered to the robot. To be successful in this role, we are looking for candidates to have the following skills and experience. We welcome
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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