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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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focus on developing a molecular- and system-level understanding of CO₂ capture and release in e-DAC systems using computational modeling and simulation. The PhD candidate will apply computational
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complex materials simulations. These agents will assist with setting up, executing, and optimizing electronic structure workflows, from standard ground-state Density Functional Theory (DFT) calculations
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Bayesian Networks (DBNs) for probabilistic risk modelling Scenario-based simulation for rare-event analysis You will be part of a dynamic, interdisciplinary research setting at one of Europe’s leading
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- Significant experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid, is a plus; - Familiarity with the basic concepts of quantum information and
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: Biosensors and Dynamic Regulation for Robust Biomanufacturing PhD enrolment: Spanish National Research Council DC3: Metabolic modelling and simulation of microbial stress responses and robustness PhD enrolment
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(max. one page) CV incl. education, experience, language skills and other skills relevant for the position Certified copy of original Master of Science diploma and transcript of records in the original
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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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quantum chemical calculations and molecular simulations Evaluating and developing molecular theories for association interactions with consideration of structural information Unifying descriptions
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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