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will play a key role in building a parallelized, agent-driven exploration system and integrating a multimodal detection pipeline, ensuring real-time performance, scalability, and deployment readiness in
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maintainability as well as monitoring of energy efficiency post occupancy. This role leads the development of commissioning standards, scopes or work, and RFPs; manages external commissioning agents; and acts as
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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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, 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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discovery methods to enable a search for explanatory multi-level agent-based models that can be calibrated to - and validated against - such empirical phenomena. Funding Notes This is a self-funded research
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position in the area of AI for Software Engineering. SCAI (https://scai.engineering.asu.edu/ ), one of the eight Fulton Schools, houses a vibrant Industrial Engineering and Computer Science Engineering
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networks. Participation in national and internationally funded research projects. Contribution to advanced digital twin and agent-based simulation platforms. Opportunities for interdisciplinary collaboration
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of medications and therapeutic agents necessary to implement treatment, disease prevention, or rehabilitative plan of care. perform skin tests, immunizations, phlebotomy and the initiation of peripheral venous
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-enabled adaptation. The aim is to develop theoretically grounded yet practically deployable algorithms that allow multi-agent robotics to operate robustly in dynamic, uncertain, and interactive environments
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using gem5 simulator as the main execution backend for the RL agent, while also investigating the potential of RTL simulation and physical RISC-V board as complementary execution nvironments. A key aspect