Vibration analysis for predictive maintenance

This is a Digital Opportunities Traineeship (DOT). If you want to apply for this internship, please remember that you have to be a student or recently graduated based in one of the 33 Programme Countries participating in Erasmus+ or the Horizon 2020 Associated Countries .
Before applying for a Digital Opportunity Traineeship we encourage you to check with your university if you are eligible for Erasmus+ traineeship. You can read more about DOT's in our information page .

General information

Duration:

6 months

Commitment:

Part-Time

Description:

We are looking for a pragmatic doer to support our product team in developing vibration analysis methods for predictive maintenance

What you‘ll work on:

Hands-on experimentation with vibration systems on technical equipment
Machine learning based analysis for vibration monitoring and fault detection
Design & deploy automation routines and integrate them in an AWS environment

What you’ll bring

Degree in engineering, computer science, applied mathematics, physics or a related area

Strong analytical and machine learning skills; excellent progamming skills ideally in Python

Enjoy electronics and connected sensor devices

Highly motivated, self-driven and proactive; fluent in English

What we offer

A dynamic work environment within an international team that is driven to simplify how we do maintenance in industrial environments. You’ll be part of our core team with the opportunity to shape how the company and its products evolve.

Compensation:

Financial compensation

Vibration analysis for predictive maintenance

Communication and Information Sciences, Engineering and/or Technology, Mathematics and/or Informatics

General information