EngD position on LLM Inference for Knowledge Graph

at  Universiteit Twente

KEY TAKEAWAYS

• 
  Hours
  40 hr.
• 
  Salary indication
  Salary gross/monthly
  based on full-time
  € 2,872
• 
  Deadline
  11 Feb 2025
  Artificial intelligence (AI) and knowledge graphs (KGs) have become transformative technologies across numerous domains, enabling advanced decision-making, data integration, and knowledge extraction. AI, particularly large language models (LLMs), excels in natural language understanding and reasoning, while KGs provide structured, interpretable representations of data that enhance the contextual relevance and reliability of AI systems. Their combination paves the way for impactful innovations in various fields, including healthcare, urban planning, environmental monitoring, and public governance.
  Research at the intersection of AI/LLMs and KGs is critical for addressing complex, data-driven challenges, especially in land administration, where reliable and interpretable data is paramount. Organizations like the Netherlands’ Cadastre, Land Registry, and Mapping Agency (Kadaster) rely on structured data to maintain legal certainty and provide insights for spatial planning and property rights. Integrating KGs and LLMs can enhance the utility of Kadaster’s datasets, enabling more advanced applications such as multi-modal data analysis, (geospatial) reasoning, and the development of trustworthy AI tools for land administration.

Some of the topics the EngD will investigate include:

• User query interpretation
• Knowledge graph prompting
• Dynamic knowledge fusion

Please refer the Job description for details