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including artificial intelligence and machine learning in our constantly changing and developing data environment. As our group provides data for many different end-users and projects the work can be very
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locations. This leads to a high variability and uncertainty in measurement results, especially when comparing different procedures, locations, parts, and designs. In this project you will learn and apply
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: Knowledge with data science/analytics and machine learning methods Familiarity with electrical grid operation and requirements Proficiency in the English language Good ability to present results in oral
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of the Danish Fixed-Term Employment Act (Lov om tidsbegrænset ansættelse). The part -time lecturer will be expected to teach in an already well-established elective course on entrepreneurial finance with special
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collaborative environment where students, postdocs, technicians, and scientists from various cultures work together on a variety of interdisciplinary projects. As the University of Copenhagen, Denmark, is a
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audio systems? In this project you will learn and develop experimental and statistical methods for small hearables and their millimetre and sub-millimetre scale components. See More Jobs Page PhD
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-desktop search.maps.scroll-zoom-message-mobile Søltofts Plads Bygn. 220, Kgs. Lyngby, 2800, DK Copy to Clipboard × Similar Jobs Postdoc in Modeling Events in Connected Human Lives - DTU Compute Kgs. Lyngby
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to have: Dedication and the desire to learn Good programming skills Strong theoretical background Knowledge of wind energy and preferably also hydrodynamics, flow, wake and turbulence modelling Ability
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nationalities are represented at the Institute, and we support an equal gender distribution. We are located in Lyngby, Hirtshals, Nykøbing Mors, and Silkeborg and have regular activities in Greenland. Learn more
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-generation energy conversion and storage devices. We have a unique opening to expand our efforts in developing our self-driving laboratory (SDL) that combines robotics-based lab automation, machine learning