Master Thesis Physically Informed Machine Learning Based System Identification in MEMS Gyroscopes
Job Description
Are you eager to connect physical insights with advanced AI? We are offering an exciting master's thesis opportunity to work on physically informed machine learning for system identification and performance modeling of MEMS gyroscopes.
• During your assignment, you will construct machine learning (ML) algorithms for system identification and performance prediction of MEMS gyroscopes.
• You will examine MEMS gyroscope data through detailed analysis.
• Furthermore, you will assess physically informed ML in comparison to other architectures.
• Moreover, you will acquire a deep physical understanding of MEMS gyroscopes to optimize your models.
• Finally, you will work with real-world sensor data to validate your findings.
Requirements
Function: Research
Experience Level: Not Applicable