Master Thesis: Knowledge Graphs and Queryable Data Warehouse for Supply Chain

About the role

Axis Communications is looking for two students to complete a joint master thesis worth 30 credits each, on building knowledge graphs and queryable data warehouses using LLM methodology for supply chain intelligence. Axis runs a complex global supply chain with data from ERP, CRM, financial and manufacturing systems, logistics platforms and internal applications; currently querying this data requires deep knowledge of the data warehouse architecture and SQL, and domain experts' knowledge lives mainly in documents and spreadsheets.

The goal is to turn expert knowledge into a structured knowledge graph so that an LLM can ask intelligent questions against the data warehouse, and to test whether such a graph outperforms simpler approaches like improved schema documentation for natural language querying and impact analysis.

Required profile

• Student of a Master's programme in Computer Science, Technical Physics, Mathematics, Industrial Engineering or an equivalent technical discipline
• Strong fundamentals in data structures, algorithms and software engineering
• Experience with Python and SQL, including complex queries and data transformation scripts
• Experience with Git and GitHub
• Experience with knowledge graphs or graph databases (Neo4j, ontologies, RDF, property graphs)
• Passion for real-world data problems and large, complex datasets; works well in pairs
• Eager to learn emerging technologies and adapt quickly

Required skills

• Python and SQL
• Git and GitHub
• Knowledge graphs or graph databases (Neo4j, RDF, property graphs)
• Nice to have: DBT or similar data transformation tools, LLMs, prompt engineering or RAG, REST/GraphQL APIs, basic supply chain concepts

Applications are accepted in Swedish or English through the posting, must include a CV and university grade summary, and are open only to students affiliated with a Swedish university or college, directly or via exchange. When applying in pairs, submit one application per student stating the co-applicant. The posting ends on 2026-11-15.