219 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Université de Bordeaux " scholarships in Netherlands
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policies and innovative projects led by teams of staff and students. We encourage you to apply for this position. Where to apply Website https://www.academictransfer.com/en/jobs/357563/phd-student-on-deep
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students. We encourage you to apply for this position. Where to apply Website https://www.academictransfer.com/en/jobs/357564/phd-student-on-hemodialysis-acc… Requirements Additional Information Website
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unsolicited services. Where to apply Website https://www.academictransfer.com/en/jobs/357447/phd-position-high-resolution-oc… Requirements Additional Information Website for additional job details https
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You will join the “Professional Learning & Technology” (PLT) section of the Faculty of Behavioural, Management & Social Sciences. The PLT section specializes in research on professional learning in and
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and understanding of complex biological systems and biodiversity. You will get the opportunity to learn about both simple and complex biological models, computer programming, data visualisation, and
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computational lens. This calls for strong expertise in computational methods, machine learning, and data modelling combined with solid knowledge of music. We particularly aim to cover a broad range of musical
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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