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PhD Studentship: LLM-Based Agentic AI: Foundations, Systems & Applications – PhD (University Funded)
reply. LLM-based agents is becoming a key part of our everyday life and work, handling multi-step actions in a variety of application domains. However, an important open challenge is making these agents
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Primary supervisor - Prof Mark Searcey One of the key problems in the development of new anticancer agents is specificity. How do you get the compound to the site of action in the body and avoid
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application! We are looking for a highly talented and motivated Ph.D. candidate to join our research team in the cutting-edge area of AI security, on the topic of “Memory Poisoning in LLM Agents: Foundations
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qualification (usually PhD). Research area: Systems of interacting particles are ubiquitous in natural and social sciences. Typically, they comprise many agents that, through intra-specific and inter-specific
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characterised at atomic resolution via crystal structures of PrfA–peptide complexes. Building on these findings, this PhD will develop peptide-based PrfA inhibitors as novel anti-Listeria agents. The project will
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at obtaining further academic qualification (usually PhD). Research area: Systems of interacting particles are ubiquitous in natural and social sciences. Typically, they comprise many agents that, through intra
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costs. The project focuses on Europe, with a detailed analysis of three selected case-study regions. Methodologically, SPHINX embraces five pillars, ranging from data collection to agent-based and
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Main supervisor: Prof. Joerg Widmer [IMDEA Networks] Co-supervisors/mentors: Prof. M. Petrova [RWTH], Dr. T. Otim [IMDEA], and Dr. X. Costa-Perez [NEC] Required profile: Telecommunication, Electrical
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-aligned Intelligence and Novel Exploration) group (Prof. I. Bogunovic) at the Department of Mathematics and Computer Science, University of Basel, is inviting applications for multiple PhD positions in
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to agent-based and computable general equilibrium modeling, led by five team members. The first three pillars concern the development of computational agent-based models to explore three different channels