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Field
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experience is a plus Strong engineering background, with previous experience in: Finite Element modelling Agent-based modelling Network modelling (systems biology) knowledge of statistics is a plus Additional
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will lead research at the intersection of crop-switching, environmental resilience, and agrifood sustainability. The candidate will develop and apply spatial analysis, remote sensing, and modeling
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engineering. Familiarity with optimization, agent-based modeling, or systems dynamics. Prior work in interdisciplinary, international, or applied research collaborations. Strong programming and data integration
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will lead research at the intersection of crop-switching, environmental resilience, and agrifood sustainability. The candidate will develop and apply spatial analysis, remote sensing, and modeling
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Researcher to join the group. The research project is concerned with the challenging problem of modeling the complex modern radio environment, where a diverse set of devices and agents share the available
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-agent systems, mathematical modelling, formal verification methods, stability metrics, agentic AI and data analytics are an advantage. Experience with large datasets, real-time systems, and integration
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, supply chain resilience, and lifecycle sustainability. The successful candidate will lead and conduct independent research in optimization, systems modeling, agent-based modeling (ABM), and network
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for Risk Forecasting, Large Language Models (LLMs), and Human-in-the-Loop AI Systems. Our aim is to advance AI for Operations by integrating next-generation AI agents and LLMs with real-world operational
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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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spatio-temporal generative models, and multimodal foundation models—including vision-language MLLMs and agentic AI frameworks—for longitudinal MRI and clinical data. Fellows will help build next-generation