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Principal Researcher - Foundation and World Models on Structured Business Data(m/w/x)
Research agenda leadership for a small squad focused on causal AI and semantic context for structured business data. PhD in Computer Science with a proven machine learning research vision required. Flexible working models, focus on health and well-being.
Requirements
- PhD in Computer Science or relevant disciplines
- Academic background in Foundation Models or ML
- Strong research vision for foundation models
- Extensive research experience with machine learning
- Ideally, experience in Causal AI
- Experience in industrial and academic collaboration
- Proficiency in Python and ML frameworks
- Ideally, experience with knowledge graphs
- Proven history of leading projects
Tasks
- Drive technical advances in foundation and world models
- Solve business problems using structured data
- Combine semantic context with large-scale business data
- Define the research agenda for a small squad
- Provide AI problem statements and frameworks to academia
- Monitor and compare novel research with internal work
- Publish research breakthroughs at top-tier conferences
- Contribute to thought leadership in structured data models
- Collaborate with domain specialists on world model training
- Align internal projects with community best practices
- Collaborate with and define new academic partnerships
- Supervise PhD students during internships and collaborations
- Develop novel benchmarks for business problems
- Create novel architectures and models for open-source release
Work Experience
- approx. 4 - 6 years
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- PyTorch
- TensorFlow
- knowledge graph technologies
Benefits
Learning & Development
- Constant learning
- Skill growth
Informal Culture
- Culture of inclusion
Healthcare & Fitness
- Focus on health and well-being
Flexible Working
- Flexible working models
Ergonomic Workplace
- Accessibility accommodations
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Principal Researcher - Foundation and World Models on Structured Business Data(m/w/x)
Research agenda leadership for a small squad focused on causal AI and semantic context for structured business data. PhD in Computer Science with a proven machine learning research vision required. Flexible working models, focus on health and well-being.
Requirements
- PhD in Computer Science or relevant disciplines
- Academic background in Foundation Models or ML
- Strong research vision for foundation models
- Extensive research experience with machine learning
- Ideally, experience in Causal AI
- Experience in industrial and academic collaboration
- Proficiency in Python and ML frameworks
- Ideally, experience with knowledge graphs
- Proven history of leading projects
Tasks
- Drive technical advances in foundation and world models
- Solve business problems using structured data
- Combine semantic context with large-scale business data
- Define the research agenda for a small squad
- Provide AI problem statements and frameworks to academia
- Monitor and compare novel research with internal work
- Publish research breakthroughs at top-tier conferences
- Contribute to thought leadership in structured data models
- Collaborate with domain specialists on world model training
- Align internal projects with community best practices
- Collaborate with and define new academic partnerships
- Supervise PhD students during internships and collaborations
- Develop novel benchmarks for business problems
- Create novel architectures and models for open-source release
Work Experience
- approx. 4 - 6 years
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- PyTorch
- TensorFlow
- knowledge graph technologies
Benefits
Learning & Development
- Constant learning
- Skill growth
Informal Culture
- Culture of inclusion
Healthcare & Fitness
- Focus on health and well-being
Flexible Working
- Flexible working models
Ergonomic Workplace
- Accessibility accommodations
About the Company
SAP
Industry
IT
Description
SAP innovations help over four hundred thousand customers worldwide work together more efficiently and use business insight more effectively.
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