Wind Turbine LTE & Data Analytics Internship

RE-double; Veenendaal; Hybrid; EUR 5,600 - 11,000; Part time

Benefits offered by this job

Internship allowance

Job summary

REdouble invites motivated Bachelor’s or Master’s students to contribute to Lifetime Extension (LTE) studies in wind energy. You will work with SCADA data, meteo measurements, and design information to quantify remaining useful life of turbines, using data analytics, load modelling, and fatigue assessment techniques.

The internship offers supervision by experienced wind-energy specialists, flexible hours, potential remote work, and a pathway to real-world impact in sustainable energy.

Qualifications

• Bachelor's or Master's student in a technical discipline.
• Interest in wind energy, structural integrity, or data analytics.
• Experience with Python or MATLAB and data analysis.
• Analytical mindset and ability to combine datasets with models.
• Good command of Dutch and/or English.

Responsibilities

• Collect, process, and analyze SCADA, meteorological, and operational wind-turbine data.
• Investigate parameters relevant for lifetime extension and remaining useful life assessments.
• Analyze operational load histories based on available data.
• Support fatigue and load assessments of wind turbine components.
• Develop or improve LTE estimation methods.
• Compare LTE methodologies from academia and industry.
• Identify uncertainties and opportunities to improve lifetime predictions.
• Prepare technical reports and present research findings.

Skills

Python

MATLAB

Data analysis

Statistics

Machine learning

Fatigue analysis

Structural dynamics

Dutch

English

Education

Bachelor's student (Mechanical Eng / Mech Eng)

Master's student (Mechanical Eng / Aerospace / Data Science)

Job description

REdouble invites motivated Bachelor’s or Master’s students to contribute to Lifetime Extension (LTE) studies in wind energy. You will work with SCADA data, meteo measurements, and design information to quantify remaining useful life of turbines, using data analytics, load modelling, and fatigue assessment techniques.

The internship offers supervision by experienced wind-energy specialists, flexible hours, potential remote work, and a pathway to real-world impact in sustainable energy.