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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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classical topics in numerical analysis, such as the analysis of nonlinear PDEs or the development of new solver- or coupling-methods including their convergence analysis, but also modeling and simulation
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smart grid). While there has been tremendous progress in formal verification of cyber-physical systems, existing approaches still require expert knowledge. The main goal of this project is to develop
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this interdisciplinary project, we are looking for a strong candidate to contribute to the development of quantum algorithms and applications, focusing on quantum walks and quantum machine learning on graph structures
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for quantum computers and develop methods and software tools dedicated to the design and realization of quantum algorithms/circuits. We see ourselves as an interface between the stakeholders building physical