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Field
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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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provides an excellent environment to publish, expand your professional network, and develop expertise at the intersection of systems modeling, sustainability, and industrial practice. Job requirements A PhD
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Postdoctoral Research Associate in Archaeology and Agent-Based Modelling ( Job Number: 25001105) Department of Archaeology Grade 7: - £38,784 - £46,049 per annum Fixed Term - Full Time Contract
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modules to farmer’s, cooperatives, extension agents, etc. Data scheduling, collection, analysis, interpretation, and presentation. Supervise Postdoc, PhD and Master students as well as interns Project
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expertise in Large Language Models (LLMs), Agentic Systems, as well as strong interdisciplinary teamwork skills and communication skills. About the Stanford NLP Group: Stanford NLP Group focuses on basic
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large-scale social media analysis, smartphone-based sensing, and agent-based modeling. Combining macro-level patterns with micro-level behavioral data, it will examine how polarized content influences
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from geomatics, spatial analysis, multi-agent modeling and simulation, and laboratory work (soil and surface formation studies; host of the Solsup platform of the EMerode service unit). General
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approaches (e.g. ODE/PDE-Modelling, Agent Based Modelling) Experience in mathematical analysis of data-driven methods Solid experience in programming (R, Matlab, Python, etc.) Competence in working in inter
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nature uses nitrogenases based on iron, vanadium, or molybdenum cofactors, synthetic systems still face fundamental obstacles in N₂ activation and functionalisation. Recent breakthroughs (e.g. Nature 2020
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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