27 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Dr" PhD positions at Aalborg University
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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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campus and one at the Aalborg campus. The themes cover key research areas of the department. Stipend: Synthetic Relighting of Real-World Environments via Generative AI and Computer Graphics Pipelines
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to support both traditional data and the unique requirements of quantum information systems (https://www.classique.aau.dk ). CLASSIQUE will address a suite of fresh research challenges defined by
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. More information about DESS can be found at: https://www.cs.aau.dk/research/Data-Engineering-Science-and-Systems How to apply Your application must include the following: o Application, stating reasons
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register and survey data. The integration of migrants and questions of potential return migration are increasingly important social issues across Europe, including Denmark. As many first-generation
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the agricultural pest, Spotted Wing Drosophila in current and future climates. This includes exploring mechanistic distribution models involving experimental data on environmental tolerances such as
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reliability. Prospective applicants for this PhD proposal should have the following qualifications: M.Sc. degree in communications engineering, mathematical engineering, electrical engineering, computer
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of these materials. Implementation of artificial intelligence (AI) and machine learning (ML) to establish the connection between the existing models and material data (both literature and the baseline established in
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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