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the general study programme Wireless communication; as per May 1, 2026, or as soon as possible thereafter. The candidate will be based in Copenhagen at the CMI Section (Communication Media and Information
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candidate is expected to hold: A master degree in biomedical engineering or computer science, Excellent programming skills (Python). Experience with data curation, large-scale datasets, and machine learning
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properties through computer simulations. The project also includes validation of materials in the lab and translating the findings into practical recommendations for use in real power-electronics environments
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data availability and design parameters. Importantly, the AI implementation should act as a facilitator of creativity, enhancing, and inspiring the early design phase rather than constraining
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dynamic, crowded environments. As a PhD candidate, you will develop methods that combine data-driven autonomy with formal safety guarantees and validate them in real time through simulation and experimental
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design and laboratory experimentation, you will first explore a broad range of sodium-oxide glass compositions using advanced computer models to predict how well ions can move through them. Based
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the movements and behavior of red deer in Vejlerne using advanced drone technology and AI-based data analysis. The work will include mapping reed bed dynamics and deer trails, comparing current patterns with
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electrical energy storage systems; energy management systems. Experience with data processing, statistical analysis and machine learning techniques is an advantage. Knowledge with Mathworks suite, C/C++ and
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to evolve classical communication networks to support both traditional data and the unique requirements of quantum information systems (https://www.classique.aau.dk). CLASSIQUE will address a suite of
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and UUV to support autonomous coordination and mission execution. This includes using relative measurements, shared environmental representations, and synchronized data exchange to enable precise and