39 data "https:" "https:" "https:" "https:" "UNIV" PhD positions at Aalborg University
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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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for the position. Do you have any questions? If you have any questions about the position, you are more than welcome to contact us. You will find contact persons at the bottom of the jobpost. Further information
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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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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
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leading the establishment of a centralized repository for genomic data and metadata, with a strong emphasis on existing and novel methods for the evaluation of genome quality, indexing and clustering