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analysis, simulation, chemometrics, control engineering, artificial intelligence, soft sensors, and process sensors. We are always looking for new technologies and new methods to monitor and optimize
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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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algebras, quantum affine algebras, algebraic Lie Theory, number theoretical aspects of representation theory, structure theory of Kac-Moody algebras, geometric/combinatorial representation theory, quiver
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, structure theory of Kac-Moody algebras, geometric/combinatorial representation theory, quiver representation theory. • Some experience with SageMath, polymake or other related mathematical software
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is expected, because large software toolboxes are used and further developed. The working language at the institute is English. Experience with targeted and optimized brain stimulation and with
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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 algorithms, and
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these proteins in probiotic bacteria and experimentally test their activity Optimize protein designs based on experimental results Develop bacterial biosensors of intra- and extra-cellular analytes Active
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) structures using high energy X-ray methods (scattering, spectroscopy, imaging) Design, optimization, and testing/benchmarking of reactors for operando studies Unravelling of relationships between catalyst
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objective of the research group ‘Crop Physiology’ is to understand the physiology of plants down to the structure and function of genes and proteins as well as relevant mechanisms, which allow optimizing
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-driven discovery of new physics experiments to test quantum-gravity and observe gravitational waves (examples here and here ) Inventing state-of-the-art AI-driven exploration, optimization, and search