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sediment management. This will be done for two case studies, namely Western Scheldt and Wadden Sea. To facilitate knowledge exchange and the learning process, interactive workshops will be organized
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have the freedom to work independently, while also contributing to a shared goal. You take a mastery-oriented approach to your own learning and development and are eager to support the learning and
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lives, learn better and function better. Are you interested in joining Behavioural and Movement Sciences? You are the kind of person who feels at home working in an ambitious faculty, with an informal
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: Within this international project, TU Delft will develop a machine learning-based forward operator to enable the assimilation of SAR imagery into the crop growth model. You will: Process SAR imagery over
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learning models (e.g., multimodal AI, large language/world models) with specific finetuning for ELEVATE; designing geographically context-sensitive urban design recommendations that promote active mobility
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Can technology learn to listen to how athletes feel, and not just to what the sensors measured? In the ASPIRE project, we develop knowledge for the new generation of sports tracking technology that
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and apply AI and machine learning methods for signal processing, image analysis, data fusion, and prediction; · build physics-informed and hybrid AI models that combine geophysical knowledge with data
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, are willing to search for answers. We advocate for an inclusive community and welcome employees with diverse backgrounds, cultures, and perspectives. If you want to learn more about working at Radboud
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on text and image feature learning for news ecosystems, analysing the complex multidimensional feature space of visual information to support data-driven journalism. This includes experiments
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will develop a design-build-test-learn cycle, combining high throughput experiments and active learning to obtain synthetic cells with the desired properties. You will integrate liquid handling robots