Description
MTU is seeking a master’s student to develop and evaluate a prototype that combines knowledge graphs and modern AI methods to enable cross-domain information access through a Digital Thread. The role involves researching knowledge-graph technologies, designing and implementing a prototype, developing a natural-language search interface using large language models, exploring agentic AI approaches, and analyzing solution quality. Applicants should have a relevant master’s degree, strong programming skills, preferably in Python, and interest in knowledge graphs, information retrieval, data architectures, and generative AI.
