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environmental challenges by autonomously adapting to a wide range of conditions in which faults may occur, strategies and mechanisms for keeping the system operational in the most extreme situations, while
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(Horizon Europe Programme). TRANSFORM investigates the efficacy of transformative practices as mechanisms for initiating and consolidating transitions in urban mobility cultures, and analyses the resulting
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practices as mechanisms for initiating and consolidating transitions in urban mobility cultures, and analyses the resulting socio-spatial effects. The successful applicant will be enrolled as a PhD Candidate
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integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
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integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
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behavior and concrete degradation mechanisms. The tasks comprise the development of the tracking system, the development of new concrete damage assessment based on spatially continuous strain datasets and
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settings. In general, the candidate will perform the following tasks: Carry out research in areas relevant to differential privacy, such as: Implementing novel differential privacy mechanisms for data