PhD Researcher in Uncertainty-Aware Deep Learning for Aerial Robotics
3 days ago
At DTU - Technical University of Denmark, we are seeking a highly skilled and motivated PhD researcher to contribute to our AUTOASSESS project. As a member of our team, you will design and develop novel deep learning techniques for semantic segmentation and probabilistic defect detection onboard aerial drones operating in confined environments.
Key Responsibilities- Conduct state-of-the-art research and investigate uncertainty-aware models that enhance inspection reliability and robustness in challenging scenarios.
- Create and curate probabilistic annotated datasets to capture ambiguous defect information.
- Leverage model outputs to derive qualitative and quantitative metrics of faults and defects.
You will collaborate with a multidisciplinary team to integrate your algorithms into a practical, next-generation aerial inspection platform. You will also stay current with advances in computer vision, machine learning, and aerial robotics.
Requirements and Qualifications- You must have a two-year master's degree or equivalent academic level.
- Prior work experience with probabilistic deep learning, Bayesian inference, and uncertainty quantification is an advantage.
We offer a rewarding and challenging job in an international environment at one of the world's leading technical universities. We strive for academic excellence in an atmosphere of collegial respect and academic freedom tempered by responsibility.
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