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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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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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latency constraints. - Federated and distributed learning for RAN hardware infrastructure management. o Knowledge of autonomous AI systems based on agents. Indicative skills/experience: - Multi-Agent
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if you have experience with safety-critical systems, multi-agent autonomy, or learning-based/data-driven/robust/adaptive control under uncertainty, supported by strong mathematical foundations. Hands
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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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developmental signaling pathways (Notch, Hippo) support tumorigenesis and might reveal novel therapeutic vulnerabilities. Every project incorporates the evaluation of novel pharmacologic agents to shepherd
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be considered an advantage if you have experience with safety-critical systems, multi-agent autonomy, or learning-based/data-driven/robust/adaptive control under uncertainty, supported by strong
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to develop state-of-the-art multi-agent communication protocols and innovative educational technologies based on it. Further, in collaboration with a postdoc, the candidate should establish models
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a paradigm shift in materials science by embedding mechanistic AI agents into physical experimentation cycles-enabling rapid, transparent, and reproducible design of advanced electrocatalysts. Main
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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 computable general equilibrium