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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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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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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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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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project “Responsible AI for the Swiss Judiciary” at ETH Zurich. The project develops and evaluates AI-based prototypes to support judicial decision-making, with a focus on real-world applicability. It
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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
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on correlation-based machine learning. When an agricultural system fails due to compounding climate extremes - like a simultaneous heatwave, drought, and ozone pollution spike - standard models can forecast the
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fragmentation. This project seeks to overcome these barriers by integrating BIM-based energy modeling, semantic data models (Ontologies), and Large Language Models (LLM) into the control workflow. The candidate
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hydrogen leaks, whether chronic or accidental, could act as a brake on our capacity to fully deploy the hydrogen-based technologies on short terms, especially as conventional mitigation measures such as