Thesis - Automated Text Interpretation for Development Requirements (all genders welcome)
Indexed description
Aufgaben
- Develop an end-to-end approach for clear development requirements
- Integrate heterogeneous data sources and types of data to extract and interpret relevant information for technical and functional requirements to provide knowledge for AI systems
- Generate a knowledge graph based on identified key information and create a requirements architecture
- Definition of embedding pipelines, indexing strategies, and optimization of data retrieval to support LLM-based knowledge access
- Documentation of integration processes and technical workflows
- Enrolled Master’s student in IT-related fields such as Business Informatics, Business Intelligence, Data Science, Computer Science, or similar
- Programming experience e.g. in Python, familiarity with data analysis libraries (e.g., pandas, NumPy)
- Experience in RAG, knowledge graphs, semantics and text interpretation, LLM-development
- Analytical and structured thinking with enthusiasm for understanding large data sets
- Possible approaches: MCP servers, vector databases, and other semantic interfaces
- Close collaboration with AI engineers, data architects, and system owners to ensure scalable, secure, and reusable connector templates
- You will agree on your internship period in close alignment with the department.
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Reference Code: N-A-112476
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