Predicting streaks based on jet angle deviation measurements

Are you a data science / AI student looking for a graduation assignment? Are you ready for the challenge to improve our categorization? We are looking for you!

Your assignment
To maintain good image quality during high volume printing, our printers employ algorithms to detect, and subsequently correct for, nozzles that aren't jetting ink properly, because when a nozzle does not jet ink properly, a light or dark line might appear on the sheet.
Every so often during printing, a sheet is printed containing special markers which allow us to measure the jet angle deviation the nozzles have at that time, but using this data to predict where light/dark lines are going to occur has proven to be very difficult with conventional algorithms.

The assignment is to design a method of detecting streaks using machine learning on jet angle deviation measurements, devising ways to verify its effectiveness, and comparing it to the algorithm that is currently being employed.

Your profile

• You are currently studying Data Science / AI, Applied Mathematics, Computer Science, or similar
• You think it’s challenging to work in a multi-disciplinary team
• You are not afraid to approach new people and ask questions
• You have good communication skills in English
• To be able to fulfil the assignment you have skills such as being able to break down complex problems, and creative thinking
• As of February, you are available for 4 to 6 months for 40 hours per week
  

What’s in it for you?

• A challenging assignment with skilled coaching
• Internship/ Graduation compensation of €500,- per month
• Travel cost compensation if you don’t have an ‘OV-weekcard’
• The possibility to network with professionals inside and outside your field of expertise, thanks to our diversity of disciplines which you will work with
  

Interested?

Are you interested in this assignment? Please click on the button 'apply now' where you can upload your resume and motivation letter.
If you would like to receive more information concerning this assignment, please contact Steef Reijntjes, steef.reijntjes@cpp.canon. If you have any questions about the internship in general, please contact careers@cpp.canon.