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Master Thesis in Validation and Optimization of Controllers Using Foundation Models(m/w/x)
Researching control system performance for nonlinear dynamical systems, evaluating advanced AI architectures for dynamic modeling. Experience with dynamic systems, simulation, machine learning, and control theory required. Work performed on-site.
Anforderungen
- Master's degree in Engineering, Computer Science, Robotics, Mathematics, or comparable
- Experience with dynamic systems, simulation, machine learning, system identification, and control theory
- Motivated self-management, clear communication of complex issues, and independent task structuring
- On-site presence required
- Fluency in English
- Enrollment at university
Aufgaben
- Focus on validating controllers for nonlinear dynamical systems
- Explore a data-driven validation approach
- Identify requirements for closed-loop simulation of dynamic systems
- Conduct a literature review on state-of-the-art foundation model architectures
- Compare foundation models for modeling dynamic systems
- Design and implement a data-driven workflow
- Develop a strategy for data selection and preparation
- Fine-tune selected foundation models
- Generate additional measurements for data when needed
- Systematically evaluate the accuracy of fine-tuned models
- Compare fine-tuned models with traditional physics-based and data-based models
- Analyze model performance, focusing on corner cases
- Integrate fine-tuned models into a closed-loop simulation environment
- Validate performance of existing controllers
- Explore optimization possibilities for controllers
- Analyze trade-offs between model accuracy, simulation speed, and computational resources
- Provide recommendations for practical applications
Ausbildung
- Laufendes Studium
Sprachen
- Englisch – verhandlungssicher
Noch nicht perfekt?
- Bosch GroupVollzeitPraktikumnur vor OrtRenningen
- Fraunhofer-Gesellschaft
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Master Thesis in Validation and Optimization of Controllers Using Foundation Models(m/w/x)
Researching control system performance for nonlinear dynamical systems, evaluating advanced AI architectures for dynamic modeling. Experience with dynamic systems, simulation, machine learning, and control theory required. Work performed on-site.
Anforderungen
- Master's degree in Engineering, Computer Science, Robotics, Mathematics, or comparable
- Experience with dynamic systems, simulation, machine learning, system identification, and control theory
- Motivated self-management, clear communication of complex issues, and independent task structuring
- On-site presence required
- Fluency in English
- Enrollment at university
Aufgaben
- Focus on validating controllers for nonlinear dynamical systems
- Explore a data-driven validation approach
- Identify requirements for closed-loop simulation of dynamic systems
- Conduct a literature review on state-of-the-art foundation model architectures
- Compare foundation models for modeling dynamic systems
- Design and implement a data-driven workflow
- Develop a strategy for data selection and preparation
- Fine-tune selected foundation models
- Generate additional measurements for data when needed
- Systematically evaluate the accuracy of fine-tuned models
- Compare fine-tuned models with traditional physics-based and data-based models
- Analyze model performance, focusing on corner cases
- Integrate fine-tuned models into a closed-loop simulation environment
- Validate performance of existing controllers
- Explore optimization possibilities for controllers
- Analyze trade-offs between model accuracy, simulation speed, and computational resources
- Provide recommendations for practical applications
Ausbildung
- Laufendes Studium
Sprachen
- Englisch – verhandlungssicher
Über das Unternehmen
Bosch Group
Branche
Engineering
Beschreibung
Das Unternehmen entwickelt hochwertige Technologien und Dienstleistungen, die das Leben der Menschen verbessern.
Noch nicht perfekt?
- Bosch Group
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Masterthesis - Reinforcement Learning approach for path following and base control(m/w/x)
Vollzeitnur vor OrtKeine AngabeStuttgart - Bosch Group
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