Denmark is a worldwide leader in the development and usage of wind turbines. Due to the increased demand for renewable energy, large amount of research and development is taking place in Denmark. A major issue in the practical implementation of large-scale windfarms is the inspection and damage assessment of wind turbine blades.
The proposed postdoc addresses current and future needs in automated and efficient inspection systems. A newly formed consortium consisting of computer vision experts, drone operators, and the national test center for windmills aims at developing a novel system for vision based damage assessment using drone base image acquisition and novel methods from machine learning in image analysis. The overall project period is three years and the proposed postdoc project is for two years.
This position gives the opportunity to conduct research at DTU Compute within the section for image analysis and computer graphics. In this section, there is a thriving research environment with around 45 academic employees. The research topics range from medical image analysis, 3D geometry processing, machine learning based classification to industrial machine vision.
Responsibilities and tasks
The postdoc will join a multi-disciplinary team working with defect detection on wind turbine blades. This team includes researchers within wind energy, experts within imaging and data acquisition using drones, and researchers within computer vision. This strong team has the ambition to develop an automated blade inspection system, that will dramatically change inspection and maintenance routines of wind turbine blades. In order to meet this goal, there is a need for automated fault detections and mapping these faults to geometric positions on the blade, and here the proposed postdoc project will play a key role. The aim is to develop state of the art image based classification techniques allowing for both external and internal defect detections using machine-learning techniques. Furthermore, knowledge about the material such as reflectance properties and 3D geometry will be part of the modeling. The postdoc will be main responsible for developing the classification models and algorithms.
Candidates should have a PhD degree or equivalent. The candidate must have knowledge and experience within computer vision or image analysis, preferably with knowledge about statistical methods for image classification. It is a further advantage if the candidate has knowledge about materials appearance modeling. The candidate must be skilled in scientific programming and have experience in computing large image datasets. It is an additional advantage if the candidate has experience in working within industry-university collaborations.
We offer an interesting and challenging job in an international environment focusing on education, research, scientific advice and innovation, which contribute to enhancing the economy and improving social welfare. We strive for academic excellence, collegial respect and freedom tempered by responsibility. The Technical University of Denmark (DTU) is a leading technical university in northern Europe and benchmarks with the best universities in the world.
Salary and terms of employment
The appointment will be based on the collective agreement with the Confederation of Professional Associations. The allowance will be agreed with the relevant union. The position is for two years starting September 1st 2017. The position is a full time postdoc at DTU Compute.
Further information may be obtained from section leader, Associate Professor Anders Bjorholm Dahl, tel.: +45 4525 3907 or Associate Professor Rasmus R. Paulsen: email firstname.lastname@example.org.
You can read more about DTU Compute on www.compute.dtu.dk.
Please submit your online application no later than Monday, July 3 2017. Applications must be submitted as one PDFfile containing all materials to be given consideration. To apply, please open the link "Apply online," fill in the online application form, and attach all your materials in English in one PDF file. The file must include:
- Application (cover letter)
- Diploma (an official translation into English)
- List of publications
Applications and enclosures received after the deadline will not be considered.
All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply.
Application Deadline : 3 July 2017
Postdoc in Computer Vision for Wind Turbine Blade Inspection : PDF
Posted on 2017-06-17 14:18:31
Please give reference of Scholarships-Links.com when applying for above scholarship.