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) Research area: Large Language Models (LLMs), knowledge graphs (KGs), commonsense knowledge Tasks: foundational or applied research in at least one of the following areas: LLMs, KGs, knowledge extraction
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research interests, relevant skills, and experience. The letter must be self-written without the use of LLMs. A Curriculum Vitae, including a full list of scientific contributions such as publications
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the application of machine learning (ML) methods or large language models (LLMs) Proficiency in Python programming and confident use of Unix/Linux environments; ideally experience with version control systems (e.g
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language models (LLMs) Proficiency in Python programming and confident use of Unix/Linux environments; ideally experience with version control systems (e.g., Git) Interest in or experience with semantic web
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-Checking, Argument Mining, Automated Planning, and Decision-Making. Training, domain adaptation, and evaluation of cutting-edge LLMs and Multi-Modal models in the cloud and on premise. Software Engineering
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-IEK3-VSA/FINE) . Furthermore, you will use and extend existing lightweight Large Language Models (LLMs) to assess future technological characteristics. Your tasks in detail: Using/Extending methods
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to reason about software (e.g., LLM agents for finding and fixing bugs) Static and dynamic program analysis (e.g., to infer specifications) Test input generation (e.g., to compare the behavior of old and new