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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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the theory of quantum graph states. Additional expertise in computational methods would be useful but is not necessary. The Postdoctoral and Senior Research Associate positions will also involve
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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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for computational biology and a track record of excellence in graph machine learning and multi-omics data integration? Look no further – an exciting Postdoc opportunity awaits you at the Novo Nordisk
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represented by a graph, which is a collection of nodes that are connected to each other by edges. The nodes represent the objects of the network and the edges represent relationships between objects. A common
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of the Postdoc Research Fellows are the following: Research: Work on novel AI/Data Science research with crucial interdisciplinary scope using machine/deep learning, generative/agentic AI, and knowledge graphs
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learning, small data learning · Active learning, Bayesian deep learning, uncertainty quantification · Graph neural networks This position involves active participation in a well-funded
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publications and presentations. Collect, analyze and graph data, conclude research projects in a timely manner, write reports, and manuscripts. Engage in career development activities, apply for dedicated
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of sparse matrix, tensor and graph algorithms on distributed and heterogenouscomputational environments. Basic Qualifications: A PhD in Computer Science, Applied Mathematics, Computational Science, or related
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career in research or academia. Participate in the University’s Individual Development Plan policy for postdoctoral scholars, have a PhD or equivalent terminal degree (such as MD, DVM, PsyD, PharmD, etc