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, availability of resources, and the needs of the Department. We thus look for applicants that have a demonstrated track record in the applications of multi-agent systems. Programming and practical experiences
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 25 days ago
leader in innovative teaching, research and public service, the University of North Carolina at Chapel Hill consistently ranks as one of the nation’s top public universities and is among is the top ten
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 hours ago
leader in innovative teaching, research and public service, the University of North Carolina at Chapel Hill consistently ranks as one of the nation’s top public universities and is among is the top ten
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of computing and healthcare. Methodologies of interest include: Multi-modal learning Foundation models, including large language models Agentic AI Multi-agent AI systems Transfer learning Self-supervised
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: the originality of the project lies in the articulation of theoretical and empirical approaches, and in the design of multi-attribute incentive devices to improve the mobility of agents based on their situation
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at the UL is EUR 85176 (full time). Where to apply Website https://www.aplitrak.com/?adid=UmVjcnVpdGluZy41MTUxMi45OTA4QHVuaXZlcnNpdHlvZmx1… Requirements Research FieldEducational sciencesEducation LevelMaster
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learning Foundation models, including large language models Agentic AI Multi-agent AI systems Transfer learning Self-supervised learning Federated learning The Postdoctoral Researcher will be primarily based
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is concerned with the challenging problem of modeling the complex modern radio environment, where a diverse set of devices and agents share the available spectrum. In this environment, it is crucial
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highly motivated. Preferred Qualifications The ideal candidate should possess knowledge and expertise in the manipulation of infectious agents, the application of ELISA, the utilization of multi-color FACS
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: 278915095 Position: Postdoctoral Associate: Integrating political economy insights into energy modeling Description: The Peng group in the School of Public and International Affairs and the Andlinger Center