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of a novel condition monitoring system. Responsibilities: Develop machine learning algorithms and methods for condition monitoring of a disruptive new main bearing technology. Analyze sensor data from
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at the Doctoral School in Medicine, Biomedical Science and Technology in accordance with the regulations of Ministerial Order No. 1039 of August 27, 2013 on the PhD Programme at the Universities and
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Danish/Scandinavian labor markets. General information It is a prerequisite for allocation of the stipend that the candidate will be enrolled as a PhD student at Doctoral School of Social Sciences and
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of Engineering and Science in accordance with the regulations of Ministerial Order No. 1039 of August 27, 2013 on the PhD Programme at the Universities and Certain Higher Artistic Educational Institutions
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. Mobilizing literature in science and technology studies(STS), media studies and social anthropology, the project aims to redefine digital breakdowns as everyday “normal” occurrences rather than perpetual
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are highly interdisciplinary and include experts within e.g. biomedical engineering, neuropsychology, pharmacology, biophysics, and medicine with industrial specialisation, and medicine. You will thus be
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functional safety, security, quantitative performance, and exploitation of modern machine learning technology. It is the overall hypothesis of S4OS that a full integration of model checking and synthesis with
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candidates with excellent qualitative and/or quantitative methodological skills. Furthermore, experience with developing experimental or quasi-experimental designs for social science research. is considered
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of Social Sciences and Humanities is mandatory. The Department of Politics& Society is organized in four disciplinary clusters and the successful applicant will be affiliated with the Global Politics
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that the candidate will be enrolled as a PhD student at the Doctoral School of Engineering and Science in accordance with the regulations of Ministerial Order No. 1039 of August 27, 2013 on the PhD Programme at