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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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this interdisciplinary project, we are looking for a strong candidate to contribute to the development of quantum algorithms and applications, focusing on quantum walks and quantum machine learning on graph structures
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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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, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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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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About us The Department of Informatics is seeking to appoint a postdoctoral research fellow with an excellent track record in knowledge graphs, semantic technologies, and machine learning. Topics
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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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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | 22 days ago
, mathematics, and data science. Collaborative projects merge traditional geographic research with advanced computational methods such as graph neural networks (GNNs) and large language models (LLMs) to explore
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, United States of America [map ] Subject Areas: Data Science, AI, Graph Theory, Optimization, Probability Theory Appl Deadline: 2025/07/30 11:59PM Position Description: Apply Position Description UNIVERSITY OF SOUTH CAROLINA
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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