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resilience for Cyber-Physical Systems (CPS). The 10 Doctoral Candidates (DC) will collaborate on modeling threat actors, developing scalable AI-based monitoring and control systems, and designing strategies
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initiatives, committees and task forces, based on expertise or experience, as assigned. Develops and maintains subject matter expertise in one or more substantive areas of law that routinely or materially
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timely research question: How can Large Language Models (LLMs) and intelligent agents support transparent, scalable, and auditable clinical data harmonization? We are particularly interested in: LLM-driven
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, especially large language models (LLMs), enable the development of interactive AI agents that can support human learning in complex, safety-critical environments. Human-centered AI in this project means
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engineering projects is increasingly complex, particularly when balancing human expertise and Large Language Models as collaborative agents. This project aims to propose a reputation-based agentic Artificial
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area of AI security, on the topic of “Memory Poisoning in LLM Agents: Foundations, Attacks, and Defenses”. Your work assignments Large language model (LLM) agents represent the next generation of
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and responsibilities The Project Expert performing as Senior AI Solutions Developerwill: Develop and implement advanced AI models, including deep neural networks, transformers, LLM-based systems
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supervision of PI Calina Copos and will engage in collaborative work with cell and developmental biologists. Expertise in agent-based models, continuum PDE descriptions, dynamical systems, and/or ML-based
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(Lua/Java), agent behavior modeling, event handling, and API-based integration with external AI systems. Experience with distributed systems, reinforcement learning, or simulation environments (e.g
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multiple AI fields, including machine learning (including deep learning, foundation models or agentic AI), human-centered AI (including social computing, multi-modal processing or robotics), digital security