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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 Nov

Key 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

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