DTU Tenure Track Researcher in Computer Vision and AI for Wind Turbine Components | Kongens Lyngby, Lyngby‐Taarbæk Municipality, Denmark | Technical University of Denmark

Position:	DTU Tenure Track Researcher in Computer Vision and AI for Wind Turbine Components
Institution:	Technical University of Denmark
Location:	Kongens Lyngby, Lyngby‐Taarbæk Municipality, Denmark
Duties:	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
Requirements:	As formal qualification you must hold a PhD degree (or equivalent); 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

Text:	DTU Tenure Track Researcher in Computer Vision and AI for Wind Turbine Components 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 As formal qualification you must hold a PhD degree (or equivalent); 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