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The Computer Vision Group is looking for an aspiring PhD to investigate multi-agentic AI, LLMs, and VLMs applied to agricultural sciences. Currently, established AI models often fail to generalize
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the field. Perform quantitative analysis and agent-based modeling of behavior. Report, discuss, and present data to the team. The position is for 36 months. Laboratory work using virtual reality (VR
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of genetic loci and chromosomal rearrangements. • Develop and analyze individual-based (agent-based) models programmed in SLiM or C++ to test the robustness of analytical results (e.g., accounting for genetic
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for Artificial Intelligence) project, where newly admitted PhD students will research and develop large language models and agentic interfaces for multilingual knowledge management, using high-quality
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-preserving techniques, and robust data curation. AI Safety: Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model experimentation and training. Science of
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curation. AI Safety: Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model experimentation and training. Science of Deep Learning: Exploring mechanistic
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curation. AI Safety: Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model experimentation and training. Science of Deep Learning: Exploring mechanistic
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solutions for the global challenges of today and tomorrow. Where to apply Website https://academicpositions.com/ad/eth-zurich/2026/phd-student-in-applied-ml-and-… Requirements Research FieldComputer
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tools developed in the last decade, and compare the networks and task dynamics for the different conditions [11]. We will moreover consider various agent-based models, developed in statistical physics
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. You will develop dynamic models and apply them, for example, to analyze sociotechnological networks and to model interactions between humans and AI agents (such as LLM-based chatbots and autonomous