Researcher in Autonomous Aerial Inspection Systems

2 days ago


Kongens Lyngby, Lyngby-Tårbæk Kommune, Denmark DTU - Technical University of Denmark Full time

Are you an expert in deep learning and computer vision? DTU Electro invites applications for a PhD position focused on developing uncertainty-aware semantic segmentation models for aerial robotic inspection. You will design cutting-edge deep learning techniques to enhance inspection reliability and robustness in visually degraded scenarios.

The AUTOASSESS project is a high-profile EU consortium that has set new standards for aerial robotic inspection. As a researcher, you will collaborate with a multidisciplinary team to integrate your algorithms into a practical aerial inspection platform. Your responsibilities will include designing novel deep learning techniques, creating probabilistic annotated datasets, and publishing your findings in top-tier conferences and journals.

We offer a rewarding and challenging job in an international environment. You will work closely with Associate Professor Evangelos Boukas and be part of a dedicated group of people at DTU Electro. Your PhD project will result in scientific publications and experimental validation of your results.

Key Responsibilities
  • Design and develop uncertainty-aware semantic segmentation models for aerial robotic inspection
  • Create probabilistic annotated datasets to capture ambiguous defect information
  • Publish research findings in top-tier conferences and journals
  • Collaborate with the AUTOASSESS project team to integrate your algorithms into a practical aerial inspection platform


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