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control and energy-management algorithms for efficient and reliable long-duration operation. Implement hardware-in-the-loop (HIL) and real-time co-simulation for validation under realistic grid scenarios
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in algorithmic design; Possess good communication skills and an excellent command of English. Additional Information Benefits We encourage high responsibility and independence while collaborating with
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feasible structural health monitoring technologies. Cost–benefit assessment of sensor deployment and measurement interpretation strategies. This is a multifaceted project at the intersection of structural
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innovation processes. Our research approach is process-oriented, using methods that range from intensive longitudinal studies with apps and sensors to in-depth embedded ethnographic research. Together
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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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algorithms for optimal operation of grid-integrated LDES; Develop a co-simulation framework to analyse LDES performance under different grid scenarios. Collaborate with consortium partners to translate
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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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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