Principal Researcher - Foundation and World Models on Structured Business Data
Role details
Job location
Tech stack
Job description
-
Drive pioneering technical advances to the field of foundation models on structured data, as well as exploring world models for solving business problems .
-
Expand the horizon of what is possible by bringing together rich semantic context with large scale business data
-
Define the research agenda for a small squad of research scientists and engineers
-
Enable academic research by providing B usiness AI relevant problem statements, frameworks and data sets .
-
Keep the pulse with novel research, providing insights into the latest research findings and making them comparable with internal work .
-
Translate applied research breakthroughs into research publications at relevant top-tier conferences and contribute to thought leadership in foundation and world models on structured data.
-
Collaborate closely with various domain specialists and data owners to understand how the data can be used for world model training.
-
Contribute to thought leadership in an entirely new field of Foundation and World Models on Structured Data.
-
Work closely with the team developing the relational pre-trained transformer (SAP-RPT-1) to exchange information and ensure that internal initiatives and project deliverables are aligned with community best practices.
-
Collaborate with established academic partners and define new collaborations with top tier academic researchers.
-
Supervise PhD students during summer internships or as part of academic collaborations.
Requirements
-
PhD in Computer Science, Artificial Intelligence, physics, mathematics or other relevant disciplines
-
Candidate must have an academic background in one of the following fields: Foundation Models / Machine Learning on large scale structured data, World Models. This should be supported by a substantial record of related publications, including recent works, at top tier conferences and a well-established network in these fields.
-
A strong research vision for foundation models on structured data, and of how world models impact the development of such foundation models
-
Extensive research experience with machine learning on structured data
-
Ideally, experience in Causal AI and how it relates to foundation models on structured data
-
Proven experience and deep understanding of the opportunities and challenges associated with collaboration between industrial and academic research
-
Proficiency in Python and experience with ML frameworks such as PyTorch , TensorFlow, or similar. Optionally, hands-on experience with (knowledge) graph 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