Bosch Group
Thesis Using Geometrical Deep Learning for Simulation(m/w/x)
Full-timeOn-siteJunior
Leinfelden-Echterdingen
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RORobert Bosch Stiftung GmbH
Master Thesis Graph Foundation Models for Enterprise Knowledge and Reasoning(m/w/x)
Renningen
Full-timeInternshipOn-site
AI/ML
Data Science
Nejo AI Summary
Developing graph foundation models for enterprise knowledge and reasoning using internal Bosch documents. Strong academic background in ML and NLP required. Hands-on experience with deep learning frameworks and familiarity with GNNs a plus.
Requirements
- Master studies in Computer Science or comparable
- Strong academic background in machine learning and NLP
- Solid understanding of foundation models and transformer architectures
- Hands-on experience with deep learning frameworks
- Familiarity with graph data structures, GNNs, and related concepts is a plus
- Bachelor’s degree in Computer Science
- Motivated and research-oriented student
- Proactive and independent approach to problem-solving
- Keen interest in problem-solving
Tasks
- Conduct comprehensive literature review on Graph Foundation Models
- Analyze benchmarks and datasets for knowledge graph construction
- Identify key methodologies for link prediction and graph analytics
- Develop innovative models for knowledge graph construction
- Experiment with GFM implementation on internal Bosch documents
- Extract structured entities and relationships from documents
- Fine-tune or prompt GFMs to infer missing links and relationships
- Translate natural language questions into formal graph queries
- Reason over graph pathways for use cases like root-cause analysis
- Evaluate model performance on academic benchmarks and Bosch datasets
- Analyze scalability, robustness, and deployment potential of methods
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Fluent
Tools & Technologies
- PyTorch
- TensorFlow
- graph neural networks
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Robert Bosch Stiftung GmbH and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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RORobert Bosch Stiftung GmbH
Master Thesis Graph Foundation Models for Enterprise Knowledge and Reasoning(m/w/x)
Renningen
Full-timeInternshipOn-site
AI/ML
Data Science
Nejo AI Summary
Developing graph foundation models for enterprise knowledge and reasoning using internal Bosch documents. Strong academic background in ML and NLP required. Hands-on experience with deep learning frameworks and familiarity with GNNs a plus.
Requirements
- Master studies in Computer Science or comparable
- Strong academic background in machine learning and NLP
- Solid understanding of foundation models and transformer architectures
- Hands-on experience with deep learning frameworks
- Familiarity with graph data structures, GNNs, and related concepts is a plus
- Bachelor’s degree in Computer Science
- Motivated and research-oriented student
- Proactive and independent approach to problem-solving
- Keen interest in problem-solving
Tasks
- Conduct comprehensive literature review on Graph Foundation Models
- Analyze benchmarks and datasets for knowledge graph construction
- Identify key methodologies for link prediction and graph analytics
- Develop innovative models for knowledge graph construction
- Experiment with GFM implementation on internal Bosch documents
- Extract structured entities and relationships from documents
- Fine-tune or prompt GFMs to infer missing links and relationships
- Translate natural language questions into formal graph queries
- Reason over graph pathways for use cases like root-cause analysis
- Evaluate model performance on academic benchmarks and Bosch datasets
- Analyze scalability, robustness, and deployment potential of methods
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Fluent
Tools & Technologies
- PyTorch
- TensorFlow
- graph neural networks
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Robert Bosch Stiftung GmbH and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
Robert Bosch Stiftung GmbH
Industry
IT
Description
Das Unternehmen gestaltet Zukunft mit hochwertigen Technologien und Dienstleistungen, die das Leben der Menschen verbessern.
Not a perfect match?
- Bosch Group
Thesis Using Geometrical Deep Learning for Simulation(m/w/x)
Full-timeOn-siteJuniorLeinfelden-Echterdingen - Bosch Group
Master Thesis Bridging the Gap between Reinforcement Learning & E2E Driving(m/w/x)
Full-timeInternshipOn-siteRenningen - Bosch Group
Master Thesis Data-Efficient Hybrid Machine Learning for Robust Vibration System Prediction(m/w/x)
Full-timeInternshipOn-siteRenningen - Bosch Group
PhD Thesis - Scalable and explainable End2End Driving Model (SEED)(m/w/x)
Full-timeOn-siteNot specifiedLeonberg - Bosch Group
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Full-timeInternshipOn-siteRenningen