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Field
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At the Fraunhofer Institute of Electronic Nanosystems (ENAS), we are leveraging AI technologies to revolutionize semiconductor fabrication processes. Our mission is to develop robust data analysis
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macro perspective. At the micro level, research questions address determinants and processes, which guide individual behaviour. At the macro level, questions on decision-making in collectives are explored
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, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service positions (TV-L E13, 100
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process optimization and model-based control. As the industry moves towards more individualized processes and products, a significant challenge is to enable accurate predictions with limited reference data
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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, machine learning
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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, machine
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Optimization and Reinforcement Learning methods for problems of design/layout Exploration of Heuristics and Data-driven Methods for the generation of design blocks Automated Test and Verification of designs
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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 microfluidic
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optimally organized processes. Your Opportunities As part of the team, you can actively shape the mobility transition. You can build an innovative network in science and industry and take on responsibility
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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, machine learning