- During your thesis you will focus on the validation of controllers for nonlinear dynamical systems and explore a data-driven validation approach.
- You will identify requirements for the closed-loop simulation of dynamic systems to enable benchmarking of different controllers.
- For model selection you will conduct a literature review to identify and compare state-of-the-art foundation model architectures for modeling dynamic systems.
- You will design and implement a data-driven workflow which includes developing a strategy for data selection data preparation and fine-tuning the selected foundation models. Additional measurements for data generation can be done when needed.
- Furthermore you will systematically evaluate the accuracy of the fine-tuned models. This also includes a comparison with traditional physics-based and data-based models and an analysis of the models performance especially in identifying of corner cases.
- Additionally you will integrate the fine-tuned model into a closed-loop simulation environment (e.g. in Python/MATLAB). This will be used to validate the performance of existing controllers and explore possibilities for their optimization.
- Finally you will analyze the trade-offs between model accuracy simulation speed and the required computational resources to provide recommendations for practical applications.
Qualifications :
- Education: Master studies in the field of Engineering Computer Science Robotics Mathematics or comparable
- Experience and Knowledge: experience with dynamic systems and simulation machine learning system identification and control theory
- Personality and Working Practice: you excel at motivated self-management communicating complex issues clearly and independently structuring tasks
- Work Routine: your on-site presence is required
- Languages: fluent in English
Additional Information :
Start: according to prior agreement
Duration: 6 months
Requirement for this thesis is the enrollment at university. Please attach your CV transcript of records examination regulations and if indicated a valid work and residence permit.
Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore we welcome all applications regardless of gender age disability religion ethnic origin or sexual identity.
Need further information about the job
Ozan Demir (Functional Department)
45250
Luiz Douat (Functional Department)
49 6
Work #LikeABosch starts here: Apply now!
#LI-DNI
Remote Work :
No
Employment Type :
Full-time
During your thesis you will focus on the validation of controllers for nonlinear dynamical systems and explore a data-driven validation approach.You will identify requirements for the closed-loop simulation of dynamic systems to enable benchmarking of different controllers.For model selection you wi...
- During your thesis you will focus on the validation of controllers for nonlinear dynamical systems and explore a data-driven validation approach.
- You will identify requirements for the closed-loop simulation of dynamic systems to enable benchmarking of different controllers.
- For model selection you will conduct a literature review to identify and compare state-of-the-art foundation model architectures for modeling dynamic systems.
- You will design and implement a data-driven workflow which includes developing a strategy for data selection data preparation and fine-tuning the selected foundation models. Additional measurements for data generation can be done when needed.
- Furthermore you will systematically evaluate the accuracy of the fine-tuned models. This also includes a comparison with traditional physics-based and data-based models and an analysis of the models performance especially in identifying of corner cases.
- Additionally you will integrate the fine-tuned model into a closed-loop simulation environment (e.g. in Python/MATLAB). This will be used to validate the performance of existing controllers and explore possibilities for their optimization.
- Finally you will analyze the trade-offs between model accuracy simulation speed and the required computational resources to provide recommendations for practical applications.
Qualifications :
- Education: Master studies in the field of Engineering Computer Science Robotics Mathematics or comparable
- Experience and Knowledge: experience with dynamic systems and simulation machine learning system identification and control theory
- Personality and Working Practice: you excel at motivated self-management communicating complex issues clearly and independently structuring tasks
- Work Routine: your on-site presence is required
- Languages: fluent in English
Additional Information :
Start: according to prior agreement
Duration: 6 months
Requirement for this thesis is the enrollment at university. Please attach your CV transcript of records examination regulations and if indicated a valid work and residence permit.
Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore we welcome all applications regardless of gender age disability religion ethnic origin or sexual identity.
Need further information about the job
Ozan Demir (Functional Department)
45250
Luiz Douat (Functional Department)
49 6
Work #LikeABosch starts here: Apply now!
#LI-DNI
Remote Work :
No
Employment Type :
Full-time
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