Master Thesis in Data-Driven Force Prediction for Rotary Grinding in the Semiconductor Industry
Core
Research project developing data-driven machine learning models to predict forces in rotary grinding processes for the semiconductor industry.
Role type
Master Thesis Researcher (Data Science/Machine Learning)
Builds
Machine learning frameworks for force prediction in rotary grinding
Domain
Semiconductor manufacturing / Mechanical Engineering / Data Science
Deliverable
production ML models
Required skills
Python programming, time-series data analysis, feature engineering, machine learning frameworks (CNN, Symbolic Regression, Mamba), performance evaluation (RMSE, MAE)
Preferred skills
Familiarity with Scikit-learn, TensorFlow, PyTorch, Pandas
Technologies
Python, Scikit-learn, TensorFlow, PyTorch, Pandas
Responsibilities
Review existing force modeling methods, implement and train ML frameworks, create comparison matrices using KPIs, document and present findings
Seniority
Master Thesis Researcher