Master Thesis in Data-Driven Force Prediction for Rotary Grinding in the Semiconductor Industry
Core
Conduct research on data-driven force prediction for rotary grinding in semiconductor manufacturing using machine learning.
Role type
Master's thesis researcher (data science/ML)
Builds
Machine learning models for force prediction in industrial grinding processes
Domain
Semiconductor manufacturing / Mechanical engineering / Data science
Deliverable
production ML models
Required skills
Python programming, time-series analysis, feature engineering, machine learning frameworks (CNN, Symbolic Regression, Mamba), statistical evaluation (RMSE, MAE)
Preferred skills
Knowledge of physical parameters in grinding, sequence-to-sequence modeling
Technologies
Python, Scikit-learn, TensorFlow, PyTorch, Pandas
Responsibilities
Review existing force modeling methods, implement and train ML frameworks, create performance comparison matrices, document and present findings
Seniority
Master's student level