Knowledge Graph
knowledge graph
Joël Ouaknine
We invite applications for a postdoctoral research position in the Foundations of Algorithmic Verification group led by Prof. Joël Ouaknine. The successful candidate will work in close collaboration with an industrial partner, delving deep into the verifications of Large Language Models (LLMs) based software programs, and contributing to bridging scientific research and applications. The project aims to develop reliable LLM-based data curation systems for data verification and data enrichment tasks such as verifying or discovering entity relationships from textual documents and/or the Web. The postdoctoral researcher will contribute to defining the methodology and develop and refine this approach, assisting in the development of a system optimized for data curation using LLMs. The position focuses on research and development of innovative verification methods to ensure the reliability and accuracy of LLM-based data curation programs and actively collaborating with industrial partners.
Spike-based embeddings for multi-relational graph data
A rich data representation that finds wide application in industry and research is the so-called knowledge graph - a graph-based structure where entities are depicted as nodes and relations between them as edges. Complex systems like molecules, social networks and industrial factory systems can be described using the common language of knowledge graphs, allowing the usage of graph embedding algorithms to make context-aware predictions in these information-packed environments.