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of TSN-based in-vehicle networks. These networks carry mixed-criticality traffic and use TSN with multiple traffic shapers and redundant communication. You will investigate methods for runtime analysis
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experimentation with Asst. Prof. Eli N. Weinstein. Your goal will be to develop fundamental algorithmic techniques to overcome critical bottlenecks on data scale and quality, enabling scientists to gather vastly
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collaboration between multiple partners, including Department of Chemical and Biochemical Engineering, DTU and industry partners – Danfoss and SaltPower. This initiative bridges academic research with industrial
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Foundation Center for Biosustainability at the Danish Technical University! This position is for you if you are an experienced scientist, and you are looking to make a difference being part of multiple
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and nanostructuring, all guided by advanced AI algorithms to optimize and understand the optical properties of light-trapping surfaces. (more information can be found in the following News post ). You
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to engage in pioneering research, collaborate with a large, dynamic and multidisciplinary team, and advance the field of quantum computing through innovative algorithms and technologies. This is an exciting
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achieve automated data driven optimization (in terms of time and quality) of polishing process parameters by application of machine learning algorithms, leading to a robust, repeatable and fast polishing
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thus including sensing systems, tool condition features selection, algorithms for automated signal preprocessing, feature extraction and decision making based on ML and AI. An integral part of