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for interdisciplinary research at the interface of energy systems, high-performance computing, and quantum computing Strong background in mathematics, optimization, numerical methods, or scientific
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hereafter. The duration of the position is three years. Your work tasks This PhD position focuses on the application of quantum computing to computational challenges in power systems with high shares of
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trade-offs between predictive performance, computational efficiency and scalability, using high-performance and cloud computing environments. Depending on the agreed research direction, you may also
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operation and very low energy consumption. The overall aim is to establish new device concepts that could contribute to high-performance classical computing and emerging brain-inspired computing hardware
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-temperature scanning tunnelling microscopy, ARPES, Kerr microscopy, femtosecond pump-probe and terahertz spectroscopy, electron microscopy, positron annihilation. Theory: high-performance computing, and
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-performance computing (HPC) systems are expected. Experience in one or more of the following areas is desirable: machine learning, agentic AI, software engineering, scientific machine learning, or
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quantum field theory Experience with programming languages, in particular C/C++/Python Experience with Linux and high-performance computing Willingness to contribute with talks to international
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scientific computing, control theory, data science, data driven methods, discrete mathematics, discretization methods, graph algorithms, high-performance computing, integral equations and nonlocal models