29 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "University of St" "St" Postdoctoral positions at Aalborg University
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work on development of wave energy and offshore wind. Most of our research is focused around work in our wave flume and basin. Further description of the group may be found here: https://vbn.aau.dk/en
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to support decision-making by integrating physical models and sensor data. These methods are validated through industrial case studies, with a particular emphasis on critical infrastructures where complexity
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and postdoc cohort positions at http://www.capex-p2x.com . The research area will be within design and modeling of pulsed power supplies utilizing power electronics technology for plasma generation
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members. Join us in making a positive impact on society! More information about the Department's research profile can be found here: https://www.communication.aau.dk. Qualification requirements Appointment
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The Department of Culture and Communication at Aalborg University’s Copenhagen campus is looking for a postdoctoral researcher in the field of Science and Technology Studies (STS). The position is
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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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. 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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The project may address national or international problems, and should do so using appropriate methods, qualitative and/or quantitative. Access to Danish data sources, such as registry data, respondents
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, but also in other study programmes at the University. You may obtain further professional information from Associate Professor Iva Ridjan Skov, +45 9940 2950, iva@plan.aau.dk You can read more on TECH
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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