SKF Maintenance Products is a dynamic unit which has been providing the bearing market with maintenance and lubrication solutions and products for forty years. A team of 35 people with entrepreneurial mind-set serves bearing users worldwide. The position we are offering represents the advantages of working within a small team, yet in an international environment. We are based at the SKF Business & Technology Park, Nieuwegein in the Netherlands.
The Diagnostics & Prognostics team within the SKF Research & Technology Development group is responsible for generating new knowledge and technology in the field of bearing and machine monitoring. The deliverables of this team are directly supporting SKF’s journey through digital transformation and will change the way we do business. By obtaining and interpreting measurement data from bearings in the field, SKF strives for a paradigm shift from unplanned to scheduled maintenance. This enables SKF to move away from classical transactional business models to performance based service contracts.
To strengthen our team in Nieuwegein we are looking for a: Researcher - Machine Learning
In this role, you will be working in multiple R&D projects. In accordance with project needs, your main responsibilities will be (but are not limited to):
SKF works to reduce friction, make things run faster, longer, cleaner and more safely. Doing this in the most effective, productive and sustainable way has made the SKF Group a leading global supplier of products, solutions and services within rolling bearings, seals, mechatronics, services and lubrication systems. Services include technical support, maintenance services, condition monitoring, asset efficiency optimization, engineering consultancy and training.
Please apply with your CV and cover letter by the 'apply' button below
Remember - you found this opportunity on Qreer.com
Micro / Nano Technology
Acoustics / Vibration Technology
2 - 5 years
5 - 10 Years
|Job Location:||Nieuwegein, Netherlands|
|Keywords:||statistics, Matlab, signal processing|