Master's Thesis on Optimizing Defect Classification and Summarization Using Machine Learning and Generative AI (SS27)
TRUMPF GmbH + Co. KG · Ditzingen
ThesisGerman needed: fluent
Still open on 3 NovKey facts
- Pay
- Attractive pay
- Duration
- 6 months
- Where you work
- Company and home
- Language needed
- German and English
- Subject you study
- Computer Science
What you'll do
- Using AI and ML techniques such as Random Forest and SVM, you classify defects and improve the reliability of machine clustering
- By leveraging GPUs and cloud services like Azure ML or Google Colab, you optimize the performance of training and prediction models
- You develop an automated system for bug report creation and linking to task boards using generative and explainable AI
- In development, you use modern tools including C# with .NET 9.0, Azure DevOps, Visual Studio 2022 or VS Code, Docker, and Python with scikit-learn, Keras, or comparable libraries
What you need
- A degree in computer science or a comparable program forms your technical basis
- You have initial experience in machine learning or AI
- Basic programming skills, preferably in Python or C#, round off your technical profile
- Good German and English skills, both written and spoken, complement your language profile
- With analytical and conceptual skills, a structured way of working, and quick comprehension, you tackle new tasks
What you get
- Attractive pay
- Flexible working hours (flextime)
- On-site or partially mobile by arrangement
- Networking opportunities with other students
- Discounted meals in the company restaurant
- TRUMPF gym and various sports groups
- Good public transport connections