Thesis on Improving Data Quality for Learning-Based Controllers

Job Description

At Bosch Corporate Research in Renningen, we are working on learning control of hydraulic cylinders for advanced excavator assistance functions.

• During your thesis, you will determine the relevant operational space for learning-based control of hydraulic cylinders for different excavators.
• You will use new concepts to detect distributional shifts of excavators and collect missing data.
• In addition, you will develop measures to reduce the computational load of V&V concepts to enable reliable lifelong learning.
• Last but not least, you will test the developed concepts using real excavators and / or using simulations with real excavator data.

Qualifications

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)

Matthias Woehrle (Functional Department)

LI-DNI