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of cellular reprogramming by introducing scalable computational methods that streamline the discovery of reprogramming targets and control strategies. A key innovation of EdgeCR is its fine-grained control
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and spatiotemporal scales, i.e., new forms of real-time automation of intelligent active grids including grid-forming converters, using distributed control and artificial intelligence (AI) based
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Pneumatic Tires, Structure-Process-Properties Relationships. As part of it, we are currently looking for a postdoc on machine learning for road characterization. How will you contribute? Do you have proven
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advanced grid-connected hardware architectures. · Implementing control loops for grid-connected power converters. · Developing gird-following and grid-forming functionalities
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different data collection methods and sensors used to gather road condition data, including TPMS (Tire Pressure Monitoring System), high-speed wheel encoders, CAN (Controller Area Network) data