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# Master Thesis in Data-Driven Force Prediction for Rotary Grinding in the Semiconductor Industry

- **Company:** Robert Bosch GmbH
- **Location:** Renningen, Germany
- **Contract:** Temporary contract
- **Skills:** Data Analysis, Computer Programming, Python (Programming Language), Machine Learning, Tensorflow, Feature Engineering, Pytorch, Convolutional Neural Networks, Pandas, Scikit Learn, Information Technology, Data Analytics
- **Published:** July 19, 2026
- **Apply:** https://www.adzuna.de/details/5803567267

## About the Role

* Education: master studies in the field of Mechanical Engineering, Data Science, Computer Science, Physics, or comparable
 * Experience and Knowledge:
 + strong programming skills in Python
 + familiarity with common data science libraries such as Scikit-learn, TensorFlow/PyTorch, and Pandas
 * Personality and Working Practice: you are highly self-motivated and enjoy tackling challenging research topics independently
 * Work Routine: your on-site presence is required
 * Languages: fluent in English and very good in German

## Description

* You will conduct a comprehensive review of existing force modeling methods for rotational grinding and explore state-of-the-art machine learning approaches for sequence-to-sequence regression on time-series data, such as Symbolic Regression, Convolutional Neural Networks, and Mamba.
 * As part of the data analysis process, you will analyze and prepare the provided time-series data, including feature engineering to extract relevant physical parameters.
 * Based on your research, you will implement and train various machine learning frameworks for force prediction.
 * To assess the developed approaches, you will create and apply a robust comparison matrix using key performance indicators such as prediction accuracy (RMSE, MAE), computational cost, and interpretability.
 * Throughout the project, you will regularly document, present, and discuss your findings and progress with the project team.


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