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benefits What you will learn: - Catalyst synthesis - Spectroscopic characterization - Electrochemical mass spectrometry - (Electrochemical) reactor design and optimization - Ion transport measurements
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on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
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in the chip design process Optimization and Reinforcement Learning methods for problems of design/layout Exploration of Heuristics and Data-driven Methods for the generation of design blocks Automated
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should enable the corresponding production processes and environments to be automatically initialized, processing areas to be generated and the optimal processing tools and their alignment to be assigned
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on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
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to the answer to this question is an intelligent, central control unit that orchestrates future autonomous vehicle fleets, optimizes road traffic, clears the road in the event of a disaster, switches traffic
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energy use more efficient. We develop new optimization methods, machine learning algorithms, and prototypical systems controlling complex energy systems like electric grids and thermal systems for a
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network adaptation is crucial for optimal perfusion. In living systems, network architecture constantly changes in response to environmental stimuli towards uniform flow to optimize transport. Combining
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the possibility of an extension. TASKS: Mathematical modeling and development of inverse methods (e.g. Bayesian inversion, optimization based methods, sparsity promoting methods based on L1-norm minimization and
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Autonomous Challenge or EDGAR . Thereby, we research current problem fields in the areas of perception, planning, control, safety and evaluation. Our goal is always to develop the optimal overall software