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compromise system integrity, safety, or performance. In this project, the research done by the PhD student will address the interaction layer in a multi-agent systems. It will focus on how to secure
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LLM Agents: Foundations, Attacks, and Defenses”. Your work assignments Large language model (LLM) agents represent the next generation of artificial intelligence (AI) sys- tems, integrating LLMs with
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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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cyber resilient AI, promoting education, knowledge sharing, and policy development. This PhD position is associated with the research theme Runtime Security Assurance. Once trained, AI models can be
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cyber resilient AI, promoting education, knowledge sharing, and policy development. This PhD position is associated with the research theme Runtime Security Assurance. Once trained, AI models can be
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, comparing it with other drug classes and countries. Applying a mixed-method approach, the project integrates qualitative case studies with quantitative Social Network Analysis, simulations (Agent-Based Models
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employment conditions. More information about the department is available at: https://www.umu.se/en/department-of-computing-science/ The department's research on responsible and human-centred artificial
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conditions. More information about the department is available at: https://www.umu.se/en/department-of-computing-science/ The department's research on responsible and human-centred artificial intelligence
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experimentally verified results is a necessary: Research Topics: Learning-Based Autonomous Systems for Field Robotics Reinforcement learning-based navigation Multi-agent coordination and communication-aware
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We are seeking a motivated and creative PhD student to explore safe and trustworthy planning under uncertainty in multi-agent systems. They will collaborate on interdisciplinary research which draws