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The Section for Electrical Energy Technology at the Department of Electrical and Computer Engineering (ECE), Aarhus University, is in a phase of rapid growth in both education and research
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campus. Working at the intersection of plasma engineering, catalysis, and renewable energy systems, the postdoc will lead experimental design, reactor operation, and data analysis for the integrated plasma
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-driven machine learning approaches, they will improve our understanding of nutrient flows in agricultural landscapes. The postdoc will contribute to the development of databases representing the current
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, electrical engineering, etc. Prior experience in (1) image processing, particularly for radiographic and computed tomographic data as well as mesh-type data, and (2) machine learning, particularly deep
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at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum
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Join us at the Department of Electrical and Computer Engineering at Aarhus University for a postdoctoral position focused on deep learning based analysis of remote sensing data for groundwater
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) that is based on redox-active organic building blocks. These building blocks enforce charge delocalization and give rise to exotic quantum states that relate to superconductivity. This project will focus
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their language of research and in English. Knowledge of other languages, including French and Haitian Kreyol will be considered an asset. Be part of a research team consisting of the PI and the other postdoc
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ecosystem models to evaluate if the respective hybrid MCL models are improving their performance. The overall project aim is on refining current aquatic ecosystem models by building models based on KGML