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Field
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digital twin applications in food, agriculture, or biosystems engineering. Familiarity with optimization, agent-based modeling, or systems dynamics. Prior work in interdisciplinary, international
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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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sustainability. The candidate will develop and apply spatial analysis, remote sensing, and modeling to evaluate the technical, environmental, and socioeconomic implications of transitioning to resilient crops in
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to the 4th February 2026. You will be investigating the safety and security implications of large language model (LLM) agents, particularly those capable of interacting with operating systems and external APIs
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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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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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function independently to develop therapeutic agents against mutant p53 and other oncoproteins using artificial intelligence, monoclonal antibodies, and DNA vaccines. The positions offer a unique team-based
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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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models and reconstruction algorithms. Develop or adapt scripts (e.g. in MATLAB, Python) to facilitate data analysis workflows. Prepare scientific reports, publications and presentations to disseminate
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applications for biomedical research. The candidate’s work will focus on developing AI methods, training AI models, and creating agentic AI workflows on DOE supercomputers and applying them to population-level