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Field
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. • Strong background in autonomous robotic systems, unmanned aerial systems (UAS), or multi-agent robotics. • Demonstrated expertise in one or more of the following areas: o Counter
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experimentation in the area of Multi-agent Agentic AI systems applied to 6G network and service management. By leveraging recent advances in LLMs and agentic tools (MCP, LangChain, etc), the project will design
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Architecture: Architect, build, and evaluate multi-agent systems powered by LLMs and machine learning, incorporating Orchestrator and Memory agents, vector databases, and knowledge graphs to enable complex goal
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applied to biomedical data. Experience or strong motivation in developing LLM-based applications, AI agents, multi-agent systems, RAG, tool-calling workflows, or autonomous scientific workflows. Familiarity
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Description Job description Game theory is rapidly gaining traction in several engineering applications as the natural framework for multi-agent decision making. Yet, unlike optimization, game theory has
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/Lab, or similar environments • Knowledge of motion planning, mapping, SLAM, frontier-based exploration, or autonomous navigation • Experience with multi-agent systems, swarm
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formation energies, adsorption energies, metal-support interactions) and correlate them against measured kinetic parameters. Contribute to multi-agent hypothesis generation and validation architectures and to
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support the development, simulation, testing, and implementation of collaborative control algorithms for multi-agent robotic systems, under the guidance of the PI and senior researchers. The work will first
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for Financial Forecasting, Data Modeling, and Multi-Agent Systems to join us in the School of Engineering at Newcastle University. You will join a collaborative research community based in Newcastle and work with
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Associate to join the Parallel Systems Lab (https://psl-ntu.github.io ) at NTU’s CCDS. The role focuses on designing, developing, and evaluating efficient, scalable systems for modern multi-agent HPC-AI