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Ultrafast lasers drive innovations from quantum technology to medical imaging, yet controlling femtosecond pulses remains a major challenge. Metamaterials are artificial structures with
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technology. ▪ Close connection to the activities of the Munich Quantum Valley with its main goal to build a quantum computer based on different platforms, to develop suitable algorithms and applications, and
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of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field
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dynamically managing power flow, improving system flexibility, and mitigating transmission constraints. However, conventional methods for PST deployment often consider sizing, placement, and control in
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characterization, and integration of machine learning to correlate synthesis conditions with functional performance. The goal is to establish predictive synthesis strategies for oxygen vacancy control, with
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position for candidates interested in interpretable AI, stochastic optimal control, deep learning and high-impact research in sustainable mobility. About us The position is located at the Systems and Control
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safe and sustainable mobility. Research environment The position is located at the Systems and Control division , with extensive collaboration with the Vehicle Safety Division and the Vehicle
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, adaptive control strategies, and hybrid energy storage solutions to address key challenges in self-powered systems under dynamic environmental conditions by: Develop machine learning or heuristic-based
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Methodologies: o Design detection and dosimetry systems tailored to the specific needs of the phosphate industry. o Innovate analytical methodologies to identify optimization opportunities. 4. Training
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and controlling defects and lay the foundation for a thermal physics-based approach to process qualification. Additive manufacturing (AM) is a rapidly evolving technology that continues to drive