- Use of machine learning techniques to analyze tests of seals including unsupervised anomaly detection
- Identification of patterns to generate insights into seal behavior during tests
- Compare analyze data to worn seals
- Transfer insights to answer product and test engineering related questions
- Master student with background in data science and technical understanding, mechanical engineer with knowledge of data science or similar
- First experience in machine learning
- MS Office
- Programming in Python
- Induction training for your new tasks: You will get to know our company, your contacts, and our structures
- A multifaceted, and interdisciplinary field of activity
- Work in multicultural environment
- A flexible work environment in our new innovation center
- Good transport connections for public transport users (3 min. S-Bahn/U-Bahn)
Job title: Master thesis student - Stuttgart, Deutschland - Trelleborg Sealing Solutions
Beschreibung
In today's research and development processes, life cycle testing of critical components is crucial to ensure reliable and sound products and services. One example of such components are sealings used in industrial applications as well as cars or airplanes. Since the effort and cost factor of humans checking the usage characteristics (e.g., wear) of seals is high, artificial intelligence (AI) as an emerging technology can help to accelerate testing and development as well as improve product quality by revealing new knowledge on preceding processing steps. To do so, sensors are installed on machines and used to collect data relevant to analyze the seal quality.
Scope of your role
What defines you
Our benefits for you
Start shaping industry from the inside
Trelleborg is an Equal Opportunity Employer, and we take pride in the diversity of our employees, valuing the special experience and expertise that people from different backgrounds bring to our business. The ability to develop ground-breaking technologies is one of our key assets and our people make it happen.