Internship / Thesis project

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

About REdouble

At REdouble, we believe that by doubling our collective efforts, we can make a significant contribution to the transition toward a sustainable society. Our name, “REdouble,” not only reflects this commitment to amplifying impact but also directly references “Renewable Energy”, the core of our expertise.

We work on improving the performance and reliability of wind energy projects by combining data, models, and engineering expertise. We support the offshore and wind energy sectors with high-quality analyses of wind and metocean conditions, measurement campaigns, and model validation studies. Our team is small, driven, and technically strong, offering plenty of room for initiative, responsibility, and personal development.

Internship Description

Many wind farms will reach the end of their original design life of 20 to 25 years in the coming years. At the same time, there is an increasing need to safely and economically extend the operation of existing wind turbines. This requires reliable methods to assess the structural condition and Remaining Useful Life (RUL) of wind turbines.

We are looking for a motivated Bachelor’s or Master’s student who would like to contribute to the development of innovative methods for Lifetime Extension (LTE) studies within the wind energy sector. During this internship, you will investigate how operational data, load models, and environmental conditions can be combined to better quantify the remaining useful life of wind turbines.

You will work with datasets such as SCADA data, meteorological measurements, and available design and operational information. Based on these datasets, you will analyze the loads experienced by a turbine throughout its operational life and investigate how this information can be used for fatigue assessments, load history reconstruction, and Remaining Useful Life analyses.

Depending on your background and interests, the focus may be on data analytics, statistical methods, load modelling, fatigue assessment, or the development of a practical LTE methodology for application within wind energy projects. The outcomes of this internship will directly contribute to current challenges related to wind turbine lifetime extension and the continued sustainability of the energy sector.

Your Responsibilities

• Collect, process, and analyze SCADA, meteorological, and operational wind turbine data.
• Investigate which parameters are most 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 methodologies for Remaining Useful Life (RUL) estimation.
• Compare different LTE methodologies from both academia and industry.
• Identify uncertainties and opportunities to improve the accuracy of lifetime predictions.
• Prepare technical reports and present research findings.

Your Profile

• You are a Bachelor’s or Master’s student in Mechanical Engineering, Applied Physics, Aerospace Engineering, Civil Engineering, Offshore Engineering, Data Science, Applied Mathematics, Computer Science, Geoinformatics, Meteorology, or a related technical discipline.
• You have an interest in wind energy, structural integrity, fatigue analysis, data analytics, or asset management.
• You have experience with programming and data analysis, for example in Python, MATLAB, or similar software.
• You possess strong analytical skills and enjoy combining complex datasets with physics-based models.
• Knowledge of statistics, machine learning, structural dynamics, fatigue assessment, or reliability engineering is considered an advantage.
• You are capable of working independently and in a structured and detail-oriented manner.
• You have a good command of Dutch and/or English.
• You have a valid EU residency permit and ideally already live in the Netherlands.

What We Offer

• A challenging internship or thesis project within a rapidly growing and innovative sector.
• Supervision by experienced specialists in wind energy, load analysis, and lifetime extension.
• The opportunity to work on real-world challenges from the wind industry.
• Flexible working hours and the possibility to work partly remotely.
• An internship allowance depending on experience and internship duration.
• The opportunity to directly contribute to the safe and cost-effective lifetime extension of wind turbines.