17 data-"https:"-"https:"-"https:"-"https:"-"Université-Laval-" Postdoctoral positions at Aalborg University in Denmark
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Measurements and Data Processing as per June 1st, 2026, or as soon as possible thereafter. The position is available for a period of 1 year, with the possibility of extension. In electronic engineering, Aalborg
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how geometry- and data-driven digital twins of wireless environments can support learning, inference, and coordination in physical AI systems such as robots, vehicles, or distributed sensing platforms
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Postdoc – Performance requirements for biobased construction materials used in the building envelope
to ensure moisture-robust designs. In addition, competencies in data processing and integration, assessment criteria development, and practical construction knowledge are necessary to translate research
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to data from various sensors and radio signals? This is the main underlying theme to be explored within this postdoctoral position. The appointed researcher will investigate how AI embedded in physical
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data storage in Iceland. Drawing on science and technology studies and, specifically, infrastructure studies (Edwards et al 2009; Star 1999), the project aims to follow moments of instability and re
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to be held after the application deadline. Further details will be communicated to shortlisted candidates. Further information Read more about our recruitment process here The appointment process at
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. The work will explore adaptive MAC designs that leverage waveform structure and context information to improve user management, access efficiency, and robustness. A key aspect of the research is the joint
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. We expect applicants to hold a PhD in a relevant field such as techno-anthropology, science and technology studies, human-computer interaction, human-robot interaction, digital health, anthropology
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will find contact persons at the bottom of the jobpost. Further information Read more about our recruitment process here The appointment process at Aalborg University involves a shortlisting process. You
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charging strategies for lithium-ion batteries. The goal is to integrate model-based (digital twin) and data-driven (AI) methods to design and experimentally validate optimized pulse charging protocols. A