Master Thesis Data-efficient Hybrid Machine Learning For Robust Vibration System Prediction
Robert Bosch GmbH
Renningen, Germany
On-site
Python (pytorch, pandas, numpy)
Fundamental machine learning concepts
Regression algorithms
You will investigate how to develop more robust and reliable predictive models for technical systems
Job Summary
You will investigate how to develop more robust and reliable predictive models for technical systems.
You will work on enhancing a machine-learning toolbox to forecast vibration-loaded systems and add crucial capabilities to learn from real-world insights, especially when measurement data is scarce.
You will openly communicate your ideas and contributions, benefiting from the exchange with colleagues within your team, experts in the field, and a broader network across various domains and locations within the company.
Matching Summary
You will investigate how to develop more robust and reliable predictive models for technical systems.
Skills & Requirements
Must-have
Python (Pytorch, Pandas, Numpy)
fundamental machine learning concepts
regression algorithms
integrate limited measurement data
simulation data integration
predict dynamic behavior
Nice-to-have
driving innovation
high degree of self-motivation
communicating progress and ideas effectively
exchange with colleagues
diversity and inclusion
Key Requirements
Master studies in Engineering, Mathematics, Physics, Computer Science