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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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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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to material, cutting tools and parts production. The PhD project will therefore focus on the development of an integrated system combining direct and indirect tool wear monitoring for reliable residual life
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PhD Position in Hydrogen/Deuterium Exchange Mass Spectrometry to Study the Regulation of Lipoprot...
. Sci. U.S.A., 122, e2420721122 (2025) Place of work: Protein Research Group (Assoc. Prof. Thomas J.D. Jørgensen), Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense
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Job Description Are you interested in developing novel machine learning methodologies that are scalable, reliable and explainable and that can address imminent challenges? Responsibilities and
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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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development and marine management. Your primary tasks will be to: Compile and harmonize data from multiple sources (e.g., EMODnet, Copernicus, fisheries surveys, citizen science). Engage with data managers and
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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
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create a closed loop pipeline able to rapidly design binders to any target and optimized for developability. The program is rooted in DALSA (DTU’s Arena for Life Science Automation), a new
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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