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description This project addresses the effective design of a military supply logistics network, composed of transportation and communication links such as roads and rail, aerial drone routes, and nodes, such as
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from reactive to proactive. The goal is to increase transparency and trust in the DNS namespace. Key research activities will include applying machine learning and graph-based techniques to uncover
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sizes and frequencies by: Measuring rock fractures from UAV data using manual and automated mapping approaches (e.g., machine learning, convolutional neural networks). Monitoring physical weathering
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carbon dioxide emissions. Mathias Peirlinck Mechanical Engineering, Delft University of Technology Mathias Peirlinck creates 'digital twins' of the human heart: personalised computer models that map
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become better versions of themselves. At BMS we do this through academic education, fundamental science and societal problem-solving. From Bachelor’s or Master’s degrees and Professional Learning
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their learning and develop reading comprehension skills? Are you eager to combine learning sciences research with classroom innovation? Then this PhD position may be of interest to you. Job description The Erasmus
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Liefvoort. For questions about this particular research project, please contact Cécile de Morrée. Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit the page about
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, including abstract geospatial workflows; design AI- and machine-learning-based methods that automatically describe and model geodata sources using textual metadata (NLP) and the geodata itself; contribute
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time to teaching in the context of the Sociology programme at Radboud University. Would you like to learn more about what it’s like to pursue a PhD at Radboud University? Visit the page about working as
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Qualification portfolio. You will be part of the WECARE research team, led by Dr Sonja Marzi (PI). Your supervisors will be Dr Sonja Marzi, Dr Tine Davids and Dr Edwin de Jong. Would you like to learn more about