19 engineering-engineering "https:" "https:" "https:" "https:" "https:" "EURAXESS" Postdoctoral positions at Aalborg University
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Monday, November 9, 2026. Interviews are tentatively planned for December 10, 2026. The positions are hosted within the Natural Language Processing (NLP) research group https://aaunlp.github.io/ at AAU
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, is under threat from growing reliance on artificial intelligence (AI) technology. While designed to assist, AI recommendations may inadvertently impede cognitive reasoning and steer decision-making
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within battery state estimation, with a particular focus on emerging sodium-ion battery technology. You will be involved in both independent and collaborative research activities in close interaction with
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and is based at Aalborg University’s campus in Aalborg. You will be part of the research group Hydrogen and Electrofuels, which is placed in the section for Thermal Engineering. The position is closely
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Engineering. The position is closely connected to our activities within developing high-fidelity models that capture the coupled thermal, chemical and electrochemical phenomena governing system performance
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topics. Your competencies You hold a PhD in a relevant field such as industrial ecology, environmental engineering, sustainability science, environmental management or a related area. You have experience
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close to 50-50% gender balance. Our working language is English. We are highly interdisciplinary and include experts within biomedical engineering, neuropsychology, pharmacology, biophysics, medicine with
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hold a PhD degree in Computer Science, Artificial Intelligence, Electrical Engineering, or a closely related field or can document equivalent scientific qualifications at PhD level. Your research profile
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fracture processes at micro and meso scales influence the structural response at an engineering scale, and to use this insight to support the design of damage tolerant composite structures. You will be
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engineering parts. This position offers a unique opportunity to drive the development of system-level digital-twin and optimization methodologies—integrating electrolyzer models with renewable generation, power