EngD Position: LiDAR-Assisted Wind Field Forecasting for Next-Gen Turbines
We are seeking a highly motivated Engineering Doctorate (EngD) Researcher to lead the development of advanced wind field forecasting methods. In this role, you will help redefine how wind turbines interact with the atmosphere, directly contributing to the global energy transition.
About the Project
Wind energy is a cornerstone of the global energy transition, but increasing the sustainability of the turbines themselves is critical. The ECOWIND project focuses on an integrated strategy to extend operational lifespans and reduce the overall weight of wind turbines. By innovating ways to lower mechanical loads on critical components and optimizing material usage, we aim to pave the way for a truly circular wind energy sector.
Your Role
A key pillar of ECOWIND is bridging the gap between remote sensing technology and real-time turbine control. Your focus will be the development of a predictive capability that allows turbines to react to the wind before it hits the blades.
Using upstream LiDAR measurements (taken several rotor diameters ahead), you will develop a wind field forecasting method, leveraging principles like Taylor’s Frozen Turbulence Hypothesis, to estimate incoming turbulent flow. You will then assess the method’s validity under real atmospheric conditions using a combination of LiDAR data and Large Eddy Simulation (LES) results.
Key Responsibilities:
- Develop and refine numerical algorithms for real-time wind field forecasting.
- Validate forecasting models against high-fidelity LES data and field measurements.
- Quantify the impact of predictive adjustments on turbine performance and load reduction.
- Communicate findings through technical reports and presentations to both academic and industrial audiences.
Information and application
Please submit your application before May 1, 2026, using the "Apply now" button, and include the following:
- A Curriculum Vitae, including contact details of two references.
- Bachelor's and Master's transcripts.
- Title and abstract of your Master's project/thesis.
- Proof of English proficiency (IELTS or TOEFL).
- A 1-minute video explaining why you are the ideal candidate for this position.
The intended starting date is June/July 2026.
For additional information about this position, you can contact Dr. Huseyin Ozdemir at h.ozdemir@utwente.nl.
Screening is part of the selection procedure
About the organisation
At the Faculty of Engineering Technology (ET), we work on engineering for impact: developing smart, sustainable, human-centred and technological solutions for societal challenges. We connect fundamental education, research and practice across five core domains: Asset & Maintenance engineering, Intelligent Manufacturing Systems, Personalised Health Technology, Resilience Engineering, and Sustainable Production, Energy and Resources.
We work on education and research in mechanical engineering, civil engineering and industrial design engineering. Together, we learn by making, creating, and innovating, addressing challenges in a solution-oriented way. Quality, connection and inclusivity are the foundation of our culture.
In our open community, students, researchers and staff collaborate with industrial and societal partners. This enables us to develop insights, applications and solutions that add value to society.
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