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Postdoc in assessing carbon sequestration potential of different wetlands as nature-based solutio...
The Department of Agroecology at Aarhus University, Denmark, is offering a postdoctoral position in assessing carbon sequestration potential of wetlands as nature-based solutions under different
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be given to seamlessly integrating an ecosystem model (LandscapeDNDC) and a farm model (to be developed, based on components from the FarmAC and other relevant models from previous and ongoing
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protocols for data format and sharing. Dissemination of the research results. Qualifications: Candidates should have a PhD degree in experimental physics, chemistry, materials science or equivalent. The core
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qualifications at the PhD level in animal science Research experience in dairy cow nutrition and feed evaluation Research experience with the use of stabile isotopes and modelling rumen flows Experience in
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receptors and HLA molecules, using lentiviral transduction. Help integrating engineered cells into sophisticated 3D skin-on-chip models. Coordinating MERFISH-based spatial transcriptomics experiments and
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project “ALPS - AI-based Learning for Physical Simulation”. Expected start date and duration of employment This is a 2–year position from 1 October 2025 or as soon possible. Job description You will be
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Two year postdoc position at Aarhus University for single molecule FRET based investigations of l...
in the target proteins. The postdoc will collect single molecule FRET data and by integration with existing atomic models establish trajectories for key conformational changes in the investigated
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Applications are invited for a 1-year post-doc position on modeling of two-phase flows for green hydrogen application at the Department of Mechanical and Production Engineering, Aarhus University
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interdisciplinary research project on production of proteins for food based on a feedstock of CO2 and energy. The positions are based at AU Viborg and/or at AU main campus and are expected to begin on 1 September
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computational models to map co-expression networks and predict systemic disease transitions. Characterise intestinal microbiome changes and their correlation with inflammatory diseases. Computational modelling