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At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging – but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.

What you`ll do:

At SAP’s Business AI Research, we are exploring the next frontier of AI methods on structured business data – graphs, tables, time series, and more. Foundation Models on Structured Data, like SAP-RPT-1, have ushered in the GenAI era for business relevant scenarios – scenarios that have so far been addressed with classical, often tree-based methods. Now, we are taking the next step. We collaborate with our existing applied research teams in creating novel benchmarks for business problems and the development of novel architectures and models, with the goal to publish benchmarks and models at scientific conferences and in the open-source community. We are working jointly with our academic partners to create ever better means of solving  real business  problems.

The Role

• Pioneer technical advances to the field of foundation models on structured data, as well as exploring world models for solving business problems.

• Gain new insights by bringing together rich semantic context with large scale business data.

• Enable academic research by providing B usiness AI relevant problem statements, frameworks and data sets .

• Keep the pulse with the 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.

• 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 partner s and s upervise PhD students during summer internships or as part of academic collaborations. 

• 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 at top tier scientific conferences .

• Extensive research experience with  machine learning on structured data , and a deep understanding on how this translates to developing foundation models on structured data

• Ideally, experience in Causal AI and how it relates to foundation models on structured data

• Proficiency in Python, and strong hands-on 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