Graduate Fellow - AI & Knowledge Mgt.

Savannah River National Laboratory is seeking a highly motivated graduate fellow to advance our AI-driven knowledge management capabilities. This fellowship is focused on building next-generation systems for intelligent information retrieval, knowledge graph construction, and multi-agent AI workflows that support complex scientific workflows. The successful candidate will bring graduate-level research experience in large language models, retrieval-augmented generation (RAG), or knowledge representation, and a passion for applying these techniques to real-world challenges across scientific and engineering domains.

• Design and implement knowledge management pipelines using large language models (LLMs), retrieval-augmented generation (RAG), and vector databases to enable intelligent information retrieval across large, multi-modal document corpora
• Develop and evaluate multi-agent AI architectures for automated reasoning, summarization, and decision support
• Build and maintain knowledge graphs and ontologies to represent complex domain relationships and support semantic search
• Collaborate with cross-functional research teams to integrate AI knowledge tools into existing scientific workflows and applications
• Author technical documentation, scientific journal articles, and internal reports communicating methods and findings to both technical and non-technical audiences
• Participate in code reviews and contribute to a shared, well-maintained research codebase
• Monitor and evaluate emerging developments in LLMs, agentic AI, and knowledge management frameworks, and assess their applicability to ongoing projects