22 density-functional-theory Postdoctoral positions at University of Groningen in Netherlands
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on the networked interactions between stakeholders in regional innovation ecosystems and assessing effects of interventions in such networks. We are interested in understanding the role of stakeholders in the set-up
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mobility (permanent, circular, temporal) and their effects on EU regions following the changing nature of regional attractiveness; (iii) it will use agent-based modelling to capture and assess the impact of
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to provide targeted interventions for improved patient outcomes. Aligned with RIS3 aims, it strengthens the Northern innovation ecosystem. The specific role of the postdoctoral researcher working in
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of the University of Groningen, offering a unique opportunity to work at the interface of academic research and industrial innovation. This project offers an excellent opportunity to contribute to a sustainable and
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Production Automation group of the RUG support this project by organizing and coordinating scientific studies that explore how people use the app that will be developed within the project. Furthermore, we will
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optimize energy systems becomes critical in steering this shift. As a Postdoctoral Researcher, you will conduct innovative research in energy modeling and optimization across diverse energy sources. The role
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. The key methodological tools for these studies are digital ethnography and conventional primary data collection (surveys, interviews). The post is part of two Horizon Europe projects: INSPIRE and EQUICARES
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with the industrial partner to this project, AkzoNobel. The research will take place at the University of Groningen, but if required, the researcher may be able to use AkzoNobel equipment and will be
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please use the following link: www.rug.nl/research/ape Qualifications Candidates should have a PhD degree in materials science and engineering. A strong background in chemical vapor deposition and
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automized positional therapy. We seek a postdoctoral researcher who is interested in Developing Data-driven control solutions for medical applications. Investigate the use of machine learning-based algorithms