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to the development of several innovative doping methods. More broadly, the research aims to understand and control how molecular interactions, ions, and charge transfer processes determine the electronic properties
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communication networks using AI-powered methods. We will advance the research front in defending future generation networks by: prevention of cyberthreats through anticipating and mitigating them, accurate
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-year project carried out in close collaboration with our industry partner. The goal is to develop methods for an ML-based decision support system for monitoring and fault diagnosis of gas turbines
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methods to provide explainable outputs from AI models in presence of attacks on the models or data, and scalable methods that move beyond feature attribution aiming for root cause analysis and decision
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, data science, or a related field. We also think you have a strong mathematical background and knowledge of optimization, particularly in areas such as complexity theory, high-order methods, acceleration
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to work well in dialogue with others is expected. Further merits Experience with mixed methods research, specifically with participatory research approaches and the close collaboration with qualitative
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of performance and stability in Na- and Zn-based batteries. The work also involves data analysis, method development, and systematic documentation of research results. Furthermore, the postdoctoral researcher is
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of the project’s digital infrastructure and analysing the Swedish folk high school based on large-scale data. You will have the opportunity to develop and apply data-driven methods, handle large digital archives