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‘Bioprime: applying biomimicry to produce restoration designs for multiple ecosystems’ at Utrecht University and the Royal Netherlands Institute for Sea Research, you will create ecosystem-specific, mass
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the development of a Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and
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to produce restoration designs for multiple ecosystems’ at Utrecht University and the Royal Netherlands Institute for Sea Research, you will create ecosystem-specific, mass-produceable structures
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Job description In the last decades, several space missions have revealed that some icy moons of the outer solar system have oceans beneath their icy crust. These findings have broadened
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on the development of new antenna and integrated circuit concepts for radar and electromagnetic modelling. The Electromagnetics (EM) and Integrated Circuit (IC) groups are involved as well as the Center for Wireless
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on the development of new antenna and integrated circuit concepts for radar and electromagnetic modelling. The Electromagnetics (EM) and Integrated Circuit (IC) groups are involved as well as the Center for Wireless
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on accurate constitutive models that describe the behavior of the molten material during forming. With the increasing demand for more complex components, a step change in model accuracy and associated material
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into the psychological factors that impair consumers' ability to detect such deceptive claims. The project will develop and test a Washing Detection Model to better understand when and why consumers are vulnerable
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of Northern Netherlands and Northwestern Germany. Agricultural soils provide a wide variety of functions, such as the supply of food and biomass, the circulation of nutrients, the regulation of water, and the
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repaired, reused, or discarded requires sophisticated condition assessment and decision-making capabilities. This PhD project tackles a critical challenge: how to develop robust machine learning models