Master’s Thesis in the Field of Data Science / Machine Learning in Injection Molding (f/m/d)
Indexed description
Some of your Benefits
Cafeteria/ Canteen: We offer fresh food on-site, both hot and cold.
Diversity & Inclusion: We focus on providing an inclusive environment and recognize our diversity contributes to our success.
Easily Reachable: Easy, low-stress access by car or public transport.
Public Transportation Allowance: Commute more affordable thanks to public transport allowance.
Employee discounts: Opportunities for deals on products and services.
Weinheim
On-Site
Freudenberg Technology Innovation SE & Co. KG
Please apply by submitting your resume and transcript of records!
You support our team as
Master’s Thesis in the Field of Data Science / Machine Learning in Injection Molding (f/m/d)
Responsibilities
- You will analyze and prepare production and process data from injection molding systems
- You will identify relevant influencing factors affecting part quality, cycle time, and scrap rates
- You will develop and implement machine learning models (e.g., regression, classification, anomaly detection)
- You will evaluate the models in terms of predictive performance and industrial applicability
- You will visualize and interpret the results for technical stakeholders
- You will derive actionable recommendations for process optimization
- You will document your results and prepare the scientific thesis
- You are currently enrolled in a degree program in Data Science, Computer Science, Mechanical Engineering, Mechatronics, Industrial Engineering, or a comparable field.
- You have strong knowledge of statistics, data science, and machine learning
- You have experience with Python and common libraries (e.g., pandas, scikit-learn, PyTorch/TensorFlow)
- You have an interest in production processes, ideally with knowledge of injection molding or manufacturing technologies
- You have very good German or English language skills, both written and spoken
- You ideally have an interest in pursuing an industrial PhD following your thesis
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