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the interfacial phenomena between water contaminants and adsorbent materials. As a member of the “Nano-Micro-Macro. Structure in Materials” research group, led by Prof. Joerg Jinschek, you will push the boundaries
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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
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Research Environment You will be part of the research group led by Assoc. Prof. Rasmus Siersbæk (Siersbaek group ) at the Dept. of Biochemistry and Molecular Biology (BMB) at SDU. The Siersbæk group is part
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academia and industry. You will be involved in the “DTU Alliance” project in collaboration with Prof. Anna Scaglione at Cornell University, with the opportunity to undertake a research stay of 5–9 months
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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
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for behavioural and security properties; efficient algorithms for model checking, learning and synthesis; improved explainability and safety of machine learning models, e.g. by integrating neural and symbolic
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better and faster decisions when assessing funding applications, ensuring the efficient and unbiased elimination of poor applications? This question can be addressed through training algorithms on past
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expertise in autonomous marine systems. The research focus will be on development, implementation and verification of novel algorithms for motion planning and control of autonomous underwater vehicles. You