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Sciences and Systems in the lab of Professor M. Bichler. We offer: - a team of young and highly motivated colleagues who are passionate about machine learning, optimization, and game theory. - strong support
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in solar energy by exploring fundamentally the controversy regarding the abnormal evaporation rate and simulate/ predict vapor production rate to guide the design of an optimized interfacial evaporator
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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 methods
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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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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 methods
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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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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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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
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technology constraints Placement & Routing for technology-independent layout generation Clocking and data synchronization Layout validation and verification Technology mapping and optimization To learn more
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efficient. We develop new optimization methods, machine learning algorithms, and prototypical systems controlling complex energy systems like electric grids and thermal systems for a sustainable future. These