Master Thesis: Physically Informed Machine Learning Based System Identification in MEMS Gyroscopes

Stack

Responsibilities

• ▹Construct machine learning (ML) algorithms for system identification and performance prediction of MEMS gyroscopes
• ▹Examine MEMS gyroscope data through detailed analysis
• ▹Assess physically informed ML in comparison to other architectures
• ▹Acquire a deep physical understanding of MEMS gyroscopes to optimize models
• ▹Work with real-world sensor data to validate findings

Requirements

• ▹Master studies in Informatics, Physics, Engineering or comparable with good grades
• ▹Experience in data-driven parameter identification; knowledge of Python, PyTorch, Pandas, and Probabilistic Modeling
• ▹Practical experience with hands-on data handling and pipeline construction
• ▹Ability to structure tasks systematically, actively explore new concepts with curiosity, and drive results with high motivation
• ▹On-site presence required
• ▹Fluent in English and good in German

Soft skills

About the company

Bosch shapes the future by inventing high-quality technologies and services that spark enthusiasm and enrich people's lives. Its promise to associates is rock-solid: they grow together, enjoy their work, and inspire each other.