94 embedded-system-"https:"-"https:"-"https:"-"https:"-"UCL" positions at Aarhus University
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The Department of Agroecology at Aarhus University, Denmark, is offering a postdoctoral position in Section for Crop Genetics and Biotechnology, starting 01-06-2026 or as soon as possible thereafter
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per 1 April 2026 or as soon as possible thereafter. This position is event limited and is part of a strategic project that aim to establish an IT-infrastructure for imaging and imaging analysis, with
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stating either how you rank as an individual student compared to other students the year you graduated ("ranks as no. 6 out of 111" or "ranks as among the best 8 percent") or if that is not possible
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radios • Clear communicator who enjoys training students Place of Employment and Place of work The place of employment will be Aarhus University, and the place of work is the Department of Geoscience
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soon as possible thereafter. The position is a five-year 10% position. As a professor at the Department of Clinical Medicine, you will be part of what is probably the largest health science research
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functional properties. The post doc position is part of the Food technology group at Department of Food Science, Aarhus University and may also include teaching and dissemination activities, as
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thereafter. The position is a fixed-term full-time position for 12 months. The department of Biomedicine prioritises diversity and a good work environment, as this is a prerequisite for groundbreaking research
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May 2026 or as soon as possible thereafter. The position is a fixed-term full-time position for 22 months. Department of Clinical Medicine As an assistant professor at the Department of Clinical
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possible thereafter. The position is a four-year temporary part time position 33,3 hours per week (90%). As a professor at the Department of Clinical Medicine, you will be part of what is probably the
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-year extension. The project is fully funded by the Independent Research Fund Denmark (DFF). The main objective of this project is to develop physics-constrained, data-driven turbulence models