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in Computer Science with a focus on visual data science. An ideal candidate has a solid education in computer science, data science or applied mathematics as well as demonstrated research experience in
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of the research, from conception, execution, analysis, publishing, and public dissemination. A solid set of field specific methods is necessary. Candidates are expected to be willing and able to contribute
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The Pioneer Center for Landscape Research in Sustainable Agricultural Futures, Land-CRAFT , at the Department of Agroecology at Aarhus University, Denmark, is offering a postdoctoral position in
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University. Our research covers physics, chemistry, microbiology, social sciences, geography, and environmental economics, addressing global challenges such as pollution control, land and water management
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at Aarhus University. Our research covers physics, chemistry, microbiology, social sciences, geography, and environmental economics, addressing global challenges such as pollution control, land and water
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of new instruments and applications. With the specialized and refined technology available, we are getting more answers and further insight about the Earth and the universe surrounding us. We contribute to
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, potentially with colour centres in diamond or other solid-state defects. We imagine that our second new colleague has experience with biophysics and nanoparticle sensors in biological systems, be it single
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dynamic research environment with access to state-of-the-art facilities and strong collaborative ties across inorganic, coordination, organometallic and enzyme chemistry. Expected competences include a
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Postdoc position to support international research and capacity-building projects employing elect...
ground-based transient electromagnetic (TEM) methods. The position is part of a Danish Ministry of Foreign Affairs funded project titled “Scaling Up Electromagnetics Surveys for Large-Scale Hydrogeological
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electroencephalographic (EEG) recordings of frequency-tagged steady-state visual evoked potentials (SSVEPs), the project will assess processing of attended and unattended colors in healthy adults performing a feature-based