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developing optimization-driven approaches to multimodal device tailoring. We are looking for someone with A PhD in Human-Computer Interaction or a closely related field Strong programming skills (e.g., Python
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. The main activities include: Designing machine learning models that can detect unusual, unsafe, or attacked operating conditions. Developing data-driven models that capture how faults and attacks spread
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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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closely related field, with a strong background in AI/ML technologies, including algorithm development, optimization, and data-driven modeling. Candidates are expected to demonstrate research leadership
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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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computer vision concepts and methods and can combine these with data-driven approaches when relevant. Experience with machine learning operations, such as model deployment, experiment tracking or scalable
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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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in e.g. programming, algorithms and data structures, software systems architecture, use of AI, data acquisition and fullstack software-development. Following the Problem-Based Learning (PBL) model, you
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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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include: developing detailed analysis plans from preregistered protocols; conducting advanced quantitative analyses of longitudinal and dyadic data; handling missing data and conducting relevant sensitivity