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for adapting large language models to tasks mixing text and structured data, such as statistical report generation and semantic search across historical statistics publications. Successful PhD candidates will
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methods to make them usable for transparent energy systems analyses. The collected data will be processed and semantically enriched using methods you develop before being transferred to a knowledge graph
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for. GUIGÓ LAB Transcription Regulation | Syntactic and Semantic Patterns in the Genome Sequence | Computational Biology | Our Research Our lab is interested in understanding the genetic and epigenetic factors
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— localization and mapping (e.g., SLAM), motion planning, and semantic perception — focusing on multimodal sensor data fusion (LiDAR, RGB-D, IMUs) for robust real-world performance. Research areas include
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one-fits-all model was proven unsuccessful. Large Language Models (LLMs) and knowledge graph models are expected to harmonize the formats and semantics but there are many open questions about their
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integration of energy systems data and models and apply data science methods to make them usable for transparent energy systems analyses. The collected data will be processed and semantically enriched using
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, Google.org, SAP, Merck, TUM Klinikum, Holtzbrinck). Diverse research topics and technologies, including: Conversational Semantic Search, Question Answering Systems, Complex Information Extraction. Fact
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differentiable algorithms for machine learning; Programming language implementation for high performance computing; Programming language semantics and foundations. Your focus will be on area 2, with your research