PhD candidate for the design of machine learning methods applied to monitoring systems at offshore platforms

We are looking for a PhD candidate focuses on the design of machine learning methods of critical components and structures of offshore wind turbines at:

• large structures as the tower


• the transition pieces


• the foundations


• other small components as bearings and hydraulic systems.

These monitoring solutions are systems based on non-destructive techniques such as ultrasounds or electromagnetic technologies.

The idea is to deploy them to work in operation while the wind turbine is producing clean energy.

These systems measure the degradation of the structure due to corrosion and other kind of phenomena, the degradation of the steel material and even the degradation of the protection systems.

To get the required precision, signal processing techniques are applied and mathematical models will be investigated to detect and identify relevant patterns.

To get more details about the project (Willow) take a look at: https://willow-project.eu/

We offer:

-Flexible schedule: 2-hour flexible start and intensive workday on Fridays and summer.
-Telework: 6 days per month
-Continuous technical and language training:
-Work-life balance
-33 vacation days per year
-Sports facilities to promote the practice of sports
-Free university tuition at the University of Navarra.
-Shopping Club: discounts in stores, travel, hotels ....
-Access to premium medical insurance at the University of Navarra Clinic.
-Good working environment based on trust and teamwork.
-Joining a leading international technology company

Degree:

Electronics engineering / Telecommunications engineering with master’s degree.

Language: Englisch C1

Software: Matlab, C/C++.