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graph theory. Qualifications Candidates with a Ph.D. in any area of cognitive neuroscience broadly defined (e.g., Psychology, Neuroscience, Computer Science, or a related field) are welcome to apply
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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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for sequence or structural data (e.g. transformers, graph neural networks) Proved experience in working independently and as part of a multidisciplinary team Evidence of strong communication and scientific
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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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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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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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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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
with biomedical data, including clinical, EHR, omics, and imaging Knowledge graphs (KGs), and integrating LLMs with KGs Multimodal LLMs Special Physical/Mental Requirements Special Instructions
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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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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