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and machine-learning methods for multi-objective optimization of efficiency, reproducibility, and operational stability Study intrinsic material stability, light-induced phase segregation, ion migration
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a techno-economic analysis, you will evaluate the planned data center. The innovative technological concept for optimizing computing power integrates both batteries and the use of hydrogen
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. MINDnet aims at addressing the challenge through a holistic optimization - from individual computing devices to the overall architecture, including a focus on applications, and training methods - across
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develop advanced models, algorithms, and control solutions for simulating, optimizing, and operating future integrated energy systems. We address the challenges arising from the increasing integration
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electron diffraction, imaging and spectroscopy, in collaboration with colleagues performing material syntheis and complementary measurements at partner locations in France and Germany. Optimizing electron
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Systems Engineering (ICE-1), our focus is on developing models and algorithms for simulating and optimizing decentralized, integrated energy systems. These systems are characterized by the high spatial and
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, scalable energy concept in which the computing infrastructure and energy system are tightly coupled and jointly optimized. During the project, a container-scale prototype will be realized, which will combine
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of electron-transparent TEM lamellae and specimens Operation and optimization of ultrafast laser systems (fs–ps range) and optical setups Characterization of electrostatic potentials and excited carrier