Researcher in Computer Vision and AI for Wind Turbine Components

Do you want to be part of a section that aims to reduce the time required for and increase the value of physical testing of wind turbine structural components by using high-performance virtual testing and cutting-edge digital technologies? Do you want to contribute to the scientific development of structural virtual testing and digitalization? 

A Tenure-Track Researcher position is available at the Structural Virtual Testing and Digitalization section at the Division of Materials and Components of DTU Wind and Energy Systems. The section’s expertise lies in multi-scale progressive failure analysis using advanced finite element models and simulation techniques. This is enabled by digital and sensor technologies such as artificial intelligence, computer vision, drones, and robotics, which are utilized for efficient, non-destructive inspection, damage characterization, damage evaluation, and health monitoring of wind turbine structural elements and components. We develop tools and software to increase both the accuracy and efficiency of structural digital representation as virtual digital twins, providing high-quality value-added services to the industry. 

Responsibilities and qualifications

The Researcher will have the opportunity to join a cross-disciplinary, international team working on developing virtual testing and digitalization methods for wind turbine structures and components. The areas of responsibility include: 

• Develop computer vision and AI models for detecting wind turbine blade damage and predicting its progression, with experimental validation carried out at DTU test facilities and with industrial partners.
• Development of thermography and computer vision-based methods for modelling and predicting static and fatigue damage evolution with a focus on wind turbine blades.
• Development of multimodal AI models that fuse data from multiple types of sensors to accurately model and predict wind turbine blade damage.
• Establish and develop data science pipelines for wind turbine blade research, including data collection, processing, and analysis. Participate in or lead software development projects related to wind turbine blade research.
• It is required that the research is published as journal papers and presented at scientific conferences. Most of the work will be done in nationally and internationally funded research projects.
• Candidates should have or develop skills to write research project proposals and lead projects.
• Teaching will be a limited part of the position. 

Good communication skills, patience, and a positive attitude to working in a team are essential requirements for the successful applicant. The daily working language is English. 

Our research teams work in several fields, and we therefore expect you to have a background and qualifications in some of the following areas: 

• Specialization in machine learning and computer vision.
• Strong skills in developing computer vision and AI models.
• Experience with thermography or thermal imaging.
• Experience in data fusion and multimodal learning.
• Experience with damage detection or industrial image anomaly detection is an advantage.
• Experience with commercial software development is an advantage.
• Experience with wind energy is an advantage.
• Ability to work independently and collaboratively in a research environment.
• Fluency in communication, reading, and writing English. 

Application procedure

Your complete online application must be submitted no later than 10 July 2025 (23:59 Danish time)

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