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, turning geodata into new answer maps. We use knowledge graphs to model these transformations and apply AI methods to scale them across large map repositories, enabling users to explore many ways maps can be
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Description Join us in seeking exciting new developments using graph theory in nearest neighbor models for active matter! Do you enjoy working with graph theory, and seeing how functions on graphs can inform
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-analytical workflows, turning geodata into new answer maps. We use knowledge graphs to model these transformations and apply AI methods to scale them across large map repositories, enabling users to explore
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from a technical and scientific perspective. The Ph.D. candidate will develop methods for uncovering DNS infrastructure dependencies at scale, relying on active measurements and graph-based analysis
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perform back-of-the-envelope calculations. You are able to create clear and visually appealing figures and graphs for scientific communication. You have basic skills in scientific writing and familiarity