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The thesis focuses on developing state-of-the-art AI-based solutions for detecting anomalies in industrial inspection data.

Your role:

Develop innovative AI-based solutions for anomaly detection in NDT applications
Conduct research on state-of-the-art methods in self-supervised learning and computer vision
Implement and optimize models using Python and popular ML/DL frameworks (e.g., PyTorch, TensorFlow)
Evaluate and compare different approaches using both quantitative and qualitative metrics
Collaborate with R&D experts to align solutions with real-world industrial requirements

Qualifikation

o become part of the ROSEN family, show us that you can work well in a team, have an analytical mind, and work independently. Please also bring the following:

A degree program (not yet completed) in field Computer Science, Data Science, Artificial Intelligence or a related field
Strong background in machine learning, deep learning, or computer vision
Hands-on experience with Python and relevant libraries/frameworks
Interest in applying AI to industrial inspection and quality assurance
Analytical, structured working style and ability to work independently
Good written and spoken English skills

Benefits