Summer Semester 2027 – fixed term of 3–6 months
Modern machine vision systems generate large volumes of image and sensor data, which are time-consuming to analyze manually and difficult to scale. At the same time, demands for quality, robustness and traceability in industrial image processing are increasing. Artificial intelligence offers new ways to automatically detect quality issues, analyze large datasets efficiently and support benchmarking processes. As part of this internship or thesis project, you will develop a concept for AI-supported quality assurance and automated analysis of machine vision systems and implement a proof of concept.
YOUR TASKS:
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You analyze existing quality assurance methods in industrial image processing and explore how AI can be used to automatically analyze large image datasets.
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You develop methods to detect and classify quality deviations, misclassifications and outliers in image data.
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You design and implement an automated analysis and benchmarking pipeline for machine vision systems.
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You develop metrics to assess image quality, detection performance and system robustness.
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You explore the use of Large Language Models (LLMs) and AI agents to interpret, aggregate and document analysis results.
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You develop dashboards and automated reports to visualize quality metrics and benchmarking results.
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You compare different machine vision solutions using real-world data and identify opportunities to improve accuracy, stability and performance.
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You document and present your findings and recommendations.
YOUR PROFILE:
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Studies in computer science, electrical engineering, data science, mathematics, robotics or a related field
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Good programming skills in Python
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Basic knowledge of machine learning, deep learning and computer vision
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Interest in industrial image processing and automated quality assurance
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Initial experience with PyTorch, TensorFlow or similar frameworks is an advantage
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Knowledge of Large Language Models (LLMs), generative AI or AI agents is an advantage
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Experience in data analysis and visualization, as well as dashboard development, is an advantage
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Independent and structured approach to work, strong analytical skills and good command of English
Contact: Sarah Disch