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Fraunhofer IOSB. You will be part of a large, interdisciplinary team from the fields of production engineering and computer science and will explore fundamentally new approaches in seven sub-projects to make
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control and optimization of electrolysis from the cell to the stack requires automated monitoring, analysis, and control of the operating parameters and processes. As part of this project, the potential
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hardware interfacing programming in Python Team-oriented and highly motivated to work in an experimental laboratory A background in quantum computing as well as experience with cryogenics, signal delivery
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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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(MUCCnet: atmosphere.ei.tum.de ) Optimization of an urban sensor network configuration for greenhouse gas and air pollutant measurements using mathematical and physical assessments Analysis of ground-based
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, computer science, mathematics, physics, or a related field with an outstanding academic record. Interest in mathematical signal processing, optimization, and/or machine learning is important. Since
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integration of vehicles into mobility and energy systems. We improve the efficiency, sustainability and economics of electric vehicles by optimizing and accelerating the integration of components up to complex