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Ronja Güldenring is a PhD student at the Technical University of Denmark (DTU), specializing in machine learning and agricultural robotics. Her recent research focuses on weed detection using advanced machine learning algorithms. Ronja has contributed to the development of datasets such as 'RumexLeaves' and 'RumexWeeds', essential for training models in agricultural settings. These datasets aim to enhance the accuracy of weed detection systems, thereby supporting sustainable agricultural practices. As part of her PhD, she is involved in projects that align with the United Nations Sustainable Development Goals, demonstrating a commitment to addressing global challenges through her research. Ronja's collaborative work includes partnerships with experts in the field, ensuring that her research has practical relevance and application. She actively participates in external collaborations to further explore innovative solutions within the agricultural domain.
This requirement applies generally across Technical University of Denmark (DTU) MSc programs including Computer Science, Applied Mathematics, and Engineering disciplines. Specific prerequisites vary by department/curriculum.