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the design of an AI test environment for open-source Large Language Models (LLMs). Research on the influence of low-frequency expert data on LLM-based systems and development of robust strategies
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defining and evaluating research progress. Our work aims to advance capabilities aligned with the ARC-AGI-3 framing, with particular emphasis on robust generalization, abstraction, and problem solving beyond
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Description: The RevEl project aims to replace PTFE-based dry binders with fluorine-free nanocomposites that combine mechanical robustness during battery operation with controlled debonding-on-demand at end
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mechanical robustness during battery operation with controlled debonding-on-demand at end-of-life to enable direct recycling. Within this project, the focus of the Department Structure Formation (SF) is on
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a closely related field with a focus on agricultural systems Solid knowledge of crop modelling and/or data-driven approaches for agricultural decision support Robust experience with Python Proven