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to the user, which pictures to show? A third possible topic is performance improvement of using a graph-based analysis and/or infrastructure. Typical RAG systems use a semantic search based on embeddings. NEO
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models and reinforcement learning models for 3D graphs of materials to explore vast inorganic chemical spaces and design synthesizable energy materials. You will couple such models with physics simulation
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, such as graph-based approaches with Retrieval-Augmented Generation (RAG) and fine-tuning of LLMs. • Contribute to developing open-source tools and code repositories • Produce high-level scientific
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), state estimation (e.g. Kalman filtering, pose graph optimization), or collaborative positioning is highly valued. Mathematical skills: Competence in mathematical modeling of dynamic systems and
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sensor integration. Experience with SLAM algorithms (vision-, acoustic-, or inertial-based), state estimation (e.g. Kalman filtering, pose graph optimization), or collaborative positioning is highly valued
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knowledge-graph groundedfactuality in LLM. The PhD students will work both independently and collaboratively within the group, and will have opportunities to engage with national and international partners