Graduation assignment - Implementation of Quality control by Computer Vision

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Graduation assignment - Implementation of Quality control by Computer Vision

Photonis Netherlands B.V. is the market leader in the development, production and sales of high-tech residual light amplifiers that are used in the industrial, scientific, medical and night vision market. In addition to production, departments such as R&D, Finance, Engineering, SCM, Purchasing, Sales and Marketing are also located in this facility. Photonis is an international organization that works on success with an enormous drive. It is our mission to extend the limits of what we can see.

(Graduation) assignment for implementation of Quality control by Computer Vision

Photonis has become interested in automation in general and utilizing intelligent computed robotics for the benefit of relieving ergonomic strain on our operators, improving consistency, efficiency, production yield and therefore saving financial costs. An image intensifier starts as an anode screen, that later will be combined with other components to form a tube. Throughout the production of the image intensifier tubes, quality inspection plays a prominent role to make products that meet Photonis’ high quality standards.

Research goal
During this internship you will work on the development of a software algorithm (based on i.e. Machine Learning, Deep Learning, Neural Networking) to obtain and analyze digital images of critical components for quality control. At the end of the graduation period, Photonis wants to have a working software algorithm to work with a camera and computer as a demonstrator for evaluation in an R&R-review in the production workshop.

We offer
A full-time internship in a booming high-tech company for a period of 6 months.


  • HBO / WO study in (for example) the field of Smart Systems Engineering or Artificial Intelligence

You can apply for a graduation internship at our facility in Roden (the Netherlands) by sending your CV and cover letter in English through the ‘apply’ button below.

By applying for this position, you agree to us providing your personal data to our internal stakeholders. We can consult your LinkedIn account.