AI, machine vision and the pharmaceutical industry – sounds like an exciting work placement, doesn’t it?

Then this role could be just the thing for you.

We are looking for a student to undertake a work placement in the field of image-based AI systems.

The focus is on a question that is highly relevant in industrial and pharmaceutical quality control: How much image data is actually needed to effectively develop, train and evaluate an AI system?

Particularly in regulated production environments, the creation and annotation of large image datasets is a time-consuming process. It is therefore important to be able to better estimate the minimum amount of data required before the project even begins.

During the internship, your work will include:

• the influence of dataset size on model performance
• relevant factors for the minimum amount of data required
• strategies for reducing data requirements whilst maintaining stable model performance
• practical guidelines for future AI projects

Using specific example projects, such as those involving rim cap inspection or nozzle inspection, you will develop well-founded recommendations for the practical deployment of image-based AI systems.

The topic combines artificial intelligence, industrial image processing, quality inspection and regulated production environments – precisely the areas where theory and practice come together in a particularly exciting way.

Are you studying Computer Science, Data Science, Machine Vision, Mechatronics, Automation Technology or a similar degree programme?