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machine learning models that can detect unusual, unsafe, or attacked operating conditions. Developing data-driven models that capture how faults and attacks spread through a system, and using them to make
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strategic initiative to further strengthen the department’s expertise in digital and AI-driven research methods. Your work tasks • Develop and carry out an independent research project under supervision
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PhD fellowship in fault tolerant quantum algorithms PhD Project in state preparation, observable extraction or noise modelling Niels Bohr Institute Faculty of Science University of Copenhagen
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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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has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct
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quantum computing programme, funded by the Novo Nordisk Foundation, that will drive research and innovations at multiple levels - from developing scalable quantum processor technologies to solutions