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communications, signal processing, or related fields at master’s level is essential. This includes a thorough understanding of the fundamentals, as well as modelling, simulation, and evaluation tools such as
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properties through computer simulations. The project also includes validation of materials in the lab and translating the findings into practical recommendations for use in real power-electronics environments
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with different control technologies, such as developing a typical grid-following type-4 wind turbine generator (WTG) simulation model, and a grid-forming type-4 WTG model without or with an energy
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knowledge and skills in machine learning - Significant experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid, is a plus; - Familiarity with the
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information theory. Experience in programming, e.g., in C++, Python or with quantum simulators, such as NetSquid, is a plus. Familiarity with the concepts of quantum information and quantum computing. Curiosity
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dynamic, crowded environments. As a PhD candidate, you will develop methods that combine data-driven autonomy with formal safety guarantees and validate them in real time through simulation and experimental
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during the interview. • CV including a list of scientific outputs (e.g. thesis, projects, papers, etc.) and contact info for two academic references • Project description • Copy of MSc diploma
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engineering, or a closely related discipline. A strong background and demonstrable interest in structural mechanics as well as engineering modelling, analysis and simulation is essential. Further, the ideal
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Python (or equivalent). Experience with glass science, battery materials and/or atomistic simulations is highly advantageous. All interested candidates are encouraged to apply, regardless of their personal
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correction and/or mitigation. Knowledge about networking protocols and distributed algorithms. Experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid