Master thesis in the field of computer vision and machine learning
ROSEN Technology and Research Center GmbH
Branche : Ingenieurwesen & Technik
- Beschäftigungsart:
- Praktikum
- Dauer:
- 6 Monate
- Beginn:
- ab sofort
- Vergütung:
- Nach Vereinbarung
- Fachbereich:
- Informatik
- Berufserfahrung:
- wünschenswert
- Einsatzort:
- Lingen (Ems)
- Home-Office möglich:
- Nein
- Kontaktaufnahme:
- Website
Stellenbeschreibung
Master thesis: AI for Anomaly Detection in Non-Destructive Testing (NDT)
We are looking for a highly motivated Master’s student to join our R&D department in the non-destructive testing (NDT) industry. The position is based in an innovative, research-oriented environment that facilitates direct interaction with experts from a wide range of disciplines and provides the ideal conditions for a high-level master's thesis.
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
Anforderungen
To 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
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