Bosch Group
Master Thesis Combining Imitation & Reinforcement Learning to Solve Automated Driving(m/w/x)
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BOBosch Group
Master Thesis Data-Efficient Hybrid Machine Learning for Robust Vibration System Prediction(m/w/x)
Renningen
Full-timeInternshipOn-site
AI/ML
Nejo AI Summary
Developing data-efficient hybrid ML models for vibration system prediction. Advanced ML techniques and Python proficiency required. Thesis completion with potential for publication.
Requirements
- Master's degree in Engineering, Mathematics, Physics, or comparable with good grades
- Good understanding of dynamics (mechanical vibrations) / mechanics
- Very good knowledge of Python (Pytorch, Pandas, Numpy etc.)
- Good to very good knowledge of fundamental machine learning concepts and algorithms, particularly relevant for regression
- High degree of self-motivation
- Independent work
- Effective communication of progress and ideas
- Driving innovation
- Fluent English and basic German
- Fluent German and very good English
- CV, transcript of records, examination regulations attached
- Valid work and residence permit if indicated
Tasks
- Investigate developing robust predictive models for technical systems
- Enhance a machine-learning toolbox for vibration-loaded systems
- Add capabilities to learn from scarce measurement data
- Research and apply advanced machine learning techniques
- Integrate limited measurement data into model training
- Develop a benchmark using simulated and new measurement data
- Utilize machine learning algorithms to predict system behavior
- Apply and evaluate chosen machine learning approaches
- Compare model performance against simulation-only models
- Communicate ideas and contributions openly
- Exchange ideas with team colleagues and experts
- Engage with a broader network across company domains and locations
Education
- Master's degree
Languages
- English – Fluent
- German – Basic
Tools & Technologies
- Python
- Pytorch
- Pandas
- Numpy
- Machine learning
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Bosch Group 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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BOBosch Group
Master Thesis Data-Efficient Hybrid Machine Learning for Robust Vibration System Prediction(m/w/x)
Renningen
Full-timeInternshipOn-site
AI/ML
Nejo AI Summary
Developing data-efficient hybrid ML models for vibration system prediction. Advanced ML techniques and Python proficiency required. Thesis completion with potential for publication.
Requirements
- Master's degree in Engineering, Mathematics, Physics, or comparable with good grades
- Good understanding of dynamics (mechanical vibrations) / mechanics
- Very good knowledge of Python (Pytorch, Pandas, Numpy etc.)
- Good to very good knowledge of fundamental machine learning concepts and algorithms, particularly relevant for regression
- High degree of self-motivation
- Independent work
- Effective communication of progress and ideas
- Driving innovation
- Fluent English and basic German
- Fluent German and very good English
- CV, transcript of records, examination regulations attached
- Valid work and residence permit if indicated
Tasks
- Investigate developing robust predictive models for technical systems
- Enhance a machine-learning toolbox for vibration-loaded systems
- Add capabilities to learn from scarce measurement data
- Research and apply advanced machine learning techniques
- Integrate limited measurement data into model training
- Develop a benchmark using simulated and new measurement data
- Utilize machine learning algorithms to predict system behavior
- Apply and evaluate chosen machine learning approaches
- Compare model performance against simulation-only models
- Communicate ideas and contributions openly
- Exchange ideas with team colleagues and experts
- Engage with a broader network across company domains and locations
Education
- Master's degree
Languages
- English – Fluent
- German – Basic
Tools & Technologies
- Python
- Pytorch
- Pandas
- Numpy
- Machine learning
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Bosch Group 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
Bosch Group
Industry
Research
Description
Das Unternehmen entwickelt hochwertige Technologien und Dienstleistungen, die das Leben der Menschen verbessern.
Not a perfect match?
- Bosch Group
Master Thesis Combining Imitation & Reinforcement Learning to Solve Automated Driving(m/w/x)
Full-timeWorking StudentOn-siteRenningen - Bosch Group
Master Thesis AI-Driven Tolerance Sensitivity Analysis of Worm Gears(m/w/x)
Full-timeInternshipOn-siteRenningen - Bosch Group
Master Thesis Bridging the Gap between Reinforcement Learning & E2E Driving(m/w/x)
Full-timeInternshipOn-siteRenningen - Bosch Group
Master Thesis Automated Scalable Deployment of Predictive Maintenance in Cloud(m/w/x)
Full-timeInternshipOn-siteStuttgart - Bosch Group
Master Thesis Automated Driving Systems(m/w/x)
Full-timeInternshipOn-siteRenningen