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based on graph theory and complex networks for the analysis of structured data. The research will investigate computational approaches for representing and analysing relationships between entities through
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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for a/an University assistant predoctoral - PhD Position in Graph Learning 39 Faculty of Computer Science Startdate: 01.05.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The PhD will be carried out at LRGP (Laboratoire
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to the large-scale nature, complexity, and heterogeneity of 6G networks, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal
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Description Are you excited about using large-scale AI to accelerate scientific discovery? Join a Horizon Europe project developing next-generation scientific foundation models that combine knowledge graphs
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 13 days ago
the replicator equation. The candidate(s) may also be required to develop computational and algorithmic platforms to link models to biological data. The project integrates dynamical systems, graph theory, linear
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20 Mar 2026 Job Information Organisation/Company LEM3 Research Field Engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 30 Jun 2026 - 00:00
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17 Mar 2026 Job Information Organisation/Company cnrs Department lem3 Research Field Engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 30 Jun
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(PhD or MSc) Our goal: Build a future-proof data platform that accelerates plant breeding research. Your colleagues: An interdisciplinary team of data engineers, researchers, and domain experts within