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PhD Researcher in Probabilistic Deep Learning for Aerial Robotics
2 weeks ago
We are seeking a highly motivated PhD researcher to join our team at DTU Electro, working on the AUTOASSESS project. As a researcher, you will design and develop novel deep learning techniques for semantic segmentation and probabilistic defect detection onboard aerial drones operating in confined, GNSS-denied environments.
The successful candidate will conduct state-of-the-art research, investigate and implement uncertainty-aware models that enhance inspection reliability and robustness in challenging, visually degraded scenarios. You will also create and curate probabilistic annotated datasets to quantitatively capture and express ambiguous defect information.
You will leverage your model outputs to derive reproducible qualitative and quantitative metrics of faults and defects, integrating statistical metrics into active inspection behaviors. Additionally, you will collaborate with a multidisciplinary team from the AUTOASSESS project to integrate your algorithms into a practical, next-generation aerial inspection platform.
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.
