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of meteorological phenomena impacting the wind energy sector, in particular with respect to wind resources and wind conditions. For example, investigating how large-scale wind farm clusters may impact atmospheric and
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approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modeling, aimed at uncover the key traits that define successful microbial biofertilizers
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(RAG) models – are shaping professional expertise and practice across diverse Danish public sector domains, especially among frontline workers, including caseworkers, service providers and welfare
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the project. Your main tasks will be: Develop and apply electromagnetic modelling techniques in combination with inverse design to study light-matter interactions in dielectric nanostructured optical surfaces
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potential for exploiting temperature gradients for producing electricity and predict their long-term performance under real operating conditions. The project also includes modeling of heat transfer and
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size while printing. For AM 17-4 PH, we will use heat treatments (in-situ as well as ex-situ) to control the aging process, with the aim of developing a tailored microstructure with layered precipitation
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-driven analysis and modeling. These are interdisciplinary positions that combine environmental engineering, materials science, and sustainability assessment. We are looking for motivated and forward