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at: https://www.umu.se/en/department-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models
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in AI and cybersecurity to develop novel solutions to cyber-resilient AI for the benefit of Swedish industry and society. The vision is to make Sweden a role model in secure trustworthy AI by
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division focusing on data-driven control methodologies. About the research project Model-based control is arguably the prime framework to perform certifiably-safe regulation of dynamical systems. However
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development related to the above areas. Publications in first class journals and highly competitive conferences in areas relevant to the work, i.e. network modelling and protocol emulation in virtualised
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management. Data from case studies (inspections, monitoring, and experimental tests) are used for model updating, calibration of safety formats, and prediction of future performance and remaining service life
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-based operando investigations of defined model catalyst surfaces for energy conversion, both in thermal and electro catalysis. The operando synchrotron studies are carried out all over Europe (Petra III
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and techniques in archaeology. The project has aimed to develop a two-part research programme. The first part focuses on developing and applying methods for 3D digital modelling, ranging from
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causal inference with structural economic modelling. Subject area The subject area for this position is economics. Fields of specialization: Labour Economics – AI and the Economy; Econometrics – Structural
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educational programs, we are now seeking a postdoctoral researcher to work on privacy for data-driven models and high-dimensional data. The position is full-time for two years, starting on 1st April 2026, or as
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storage, and optics. From AI modelling of materials and biological complexity to the design of multifunctional micro- and nano systems, we combine theory, fabrication, and innovation to tackle challenges in