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at the Copenhagen campus and one at the Aalborg campus. The themes cover key research areas of the department. Stipend no. 3: Data-driven methods for design and operation of human-centric energy-optimized indoor
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analysis utilizing methods rooted in artificial intelligence (i.e. machine learning and deep learning). The analysis will be the basis for developing a predictive model to help select the most optimal method
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systems can augment professionals’ creativity toward concurrent optimization of human health and energy efficiency. This PhD position will combine fieldwork in real-world architectural settings with human
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of exploiting the synergies between different research disciplines and technologies. You will be part of an endeavour to optimize and boost innovation and advance the scientific area of biomedical and neural
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simulation-assisted performance feedback regarding initial design concepts. We will explore how AI systems can augment professionals’ creativity toward concurrent optimization of human health and energy
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to explore GNSS Reflectometry (GNSS R) as a novel, low cost, low power bistatic remote sensing technique optimized for nanosatellite platforms. GNSS R leverages signals of opportunity from existing
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and optimization methods for Earth observation satellite networks with sensing, computing, and communication capabilities. The goal is to characterize the trade-offs between sensing accuracy, computing
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interest in the topic, even if their background does not match every qualification listed above. Stipend 2: Data-driven modeling and optimization for efficient and secure-by-design Power Electronics (Aalborg
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, mathematical engineering, acoustics, machine learning or similar; Solid mathematical and analytical skills, including signal processing, optimization, machine learning or information theory; Experience in
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Optimization" and the PhD Student will be positioned to the section for “Applied Power Electronic Systems”. How to apply Your application must include the following: Application, stating reasons for applying and