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and Mechanical Engineering (DTU Construct). In this role, you are advancing innovation by integrating material science, advanced processing techniques, and modelling to gain a comprehensive
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-based simulation model for assessing future mobility technologies in the Greater Copenhagen region. Explore the development of machine-learning based scenario discovery for future mobility policy design
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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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farm-scale modelling of nutrient flows. Food security, climate change and loss of biodiversity represent three of today’s major societal challenges. Finding solutions for all these challenges requires
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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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employees are internationals. In total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research
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tasks will be: Develop and apply electromagnetic modelling techniques in combination with inverse design to study light-matter interactions in dielectric nanostructured optical surfaces. Evaluate optical