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to develop a knowledge-aware and event-centric framework for natural language understanding, in which event graphs are built as reading progresses; event representations are learned with the incorporation
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15+ researchers and PhD students in the area of knowledge graphs. The role covers research in the areas mentioned above, as well as the production of scientific publications and application showcases
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graph neural networks for complex sensor networks such as those involved in brain imaging Develop and test data-driven methods for image and video processing for microendoscopy. Key Duties and
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robots. They will be working with a team composed of PhD students, Research Assistants and Postdocs that is developing novel multi-robot architectures for practical, real-world settings. Current solutions
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well as methods for inferring genealogical structures such as ancestral recombination graphs (ARGs) and leveraging them to study heritable traits and human evolution. Applicants should hold a be near completion of
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the collective agreement Supervision of students and PhD students Participation in external fundraising activities Involvement in the organisation of meetings, conferences, symposiums Involvement in the department
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to collaborators as well as broader audiences through e.g. conference presentations. Candidates must hold a PhD degree in supramolecular chemistry, and will have experience in the synthesis, modification, analysis