Establish and manage research collaborations with academia, industry and commercial partners
Contribute pioneering technical advances to the combination of knowledge graphs and large language models, including hands-on contributions to model code
Enable academic research by providing Business AI relevant problem statements, frameworks and data sets
Keep the pulse with the research, providing insights into the latest research findings and making them comparable with internal work
Translate project innovations into research publications and contribute to thought leadership in large language models and Generative AI.
Work closely with the knowledge graph team to exchange information and ensure that internal initiatives and project deliverables are aligned with community best practices.
What you bring
PhD or Master’s degree in Computer Science, Artificial Intelligence, physics, mathematics or other relevant disciplines
Extensive experience with Knowledge Graphs as well as large language models (e.g. graph embeddings)
Proven experience and deep understanding of the opportunities and challenges associated with collaboration between industrial and academic research
Candidate must have an academic background in one of the following fields: LLMs, Foundation Models, or Knowledge Graphs. This should be supported by a substantial record of related publications, including recent works, and a well-established network in these fields.
Proficiency in Python, and experience with ML frameworks such as PyTorch, TensorFlow, or similar. Optionally, hands-on experience with RDF, Neo4j, TypeDB, PyG or similar technologies
Ideally, professional experience with the combination of knowledge graphs and large language models in ERP domain
Proven history of leading projects with a strategic mindset complemented by superior organizational abilities