21 development-"https:"-"https:"-"https:"-"BBMRI-ERIC" Postdoctoral positions at Aalborg University in Denmark
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and is available from 1 May 2026 or as soon as possible thereafter. You will join the Section for Electric Power Systems and Microgrids at the Department of Energy and contribute to developing future
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or soon thereafter. Your work tasks The position focuses on experimental development of cement-based functional materials within a newly established interdisciplinary platform integrating cement chemistry
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Aalborg. Your work tasks The postdoctoral candidate will develop and evaluate interactive generative AI prototypes that serve as creativity support tools for architectural design practice. Findings will
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in complex in-situ environments. The key responsibility of the position is to develop post-processing methods to extra essential features from the collected measurement data despite drone positional
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marine management. In surveying and land use, sustainability is reflected in our efforts in nature restoration and climate adaptation. As society continues to develop digitally, we also focus
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: • Develop AI-driven control strategies for grid-forming inverters to enhance grid flexibility, reliability and stability. • Apply machine learning and AI tools for the battery system health estimation
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++) Knowledge of the fundamentals of ML/AI algorithms for communications and networking, and their implementation A creative mindset and curiosity to research and develop new solutions with highly skilled
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advanced modelling, data analysis, and algorithmic development. Your tasks will support our core research focus of mathematical and computational approaches to design and implement solution algorithms, with
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. The objective is to develop models and algorithms that capture spatial variability, uncertainty, and communication constraints, and to understand how these factors influence perception, adaptation, and
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entities, such as robots, vehicles, or sensors, forms internal representations of space, time, and motion when interacting in complex non-stationary environments. The objective is to study and develop models