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; survey design and online experimental methods; quantitative data analysis, preferably including choice modelling, willingness-to-pay analysis, segmentation, multivariate statistics, or related methods
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must include: a presentation of an original research question a description of the initial theoretical framework and method a presentation of the proposed material a work plan for the project Application
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statistics, AI and machine learning methods, including demonstrated experience in analysing multiple global change drivers, e.g. land use intensity, climate change, nitrogen deposition. Proven capability
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team, Aarhus University and MAX IV. Depending on the candidate’s interests and expertise, research activities may include studies of functional materials, advanced crystallographic methods, automated and
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and work in the interface of basic cellular biology /virology and experimental clinical medicine trials meeting the challenges of developing methods to the highest international scientific standards As
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instruments, with data obtained with DNA methods and data obtained with a Hirst trap. • Numerical models used by the group covers the particle dispersion model HYSPLIT in combination and the numerical models
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candidate will have an existing research profile that uses ethnographic methods to explore questions relevant to the social and ecological effects of livestock and agricultural infrastructures on landscapes
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genetic basis of plant–microbe interactions, with a particular emphasis on data integration across plant species and data types (genomics, transcriptomics). Design, adapt and use deep learning methods
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ability to conduct independent scientific research Strong methodological competence in qualitative or ethnographic research methods a track record or clear potential for publishing in international peer
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experiments; developing the computational evaluation infrastructure; and contributing interpretability-based detection methods to the joint oversight framework. In addition to the PIs and this postdoctoral