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• Develop innovative methods for uncertainty quantification in autonomous vehicle perception (e.g., object detection, semantic segmentation, scene understanding)
• Conduct AI research in computer vision and deep learning, focusing on visual language models and model calibration
• Integrate and evaluate uncertainty metrics in automated driving systems
• Work with synthetic and real-world datasets, including challenging scenarios like adversarial inputs and edge cases
• Publish research findings, participate in international conferences and contribute to patent applications where applicable
• Collaborate in preparing funding applications, supervise theses, and support the professorship's research and teaching endeavors

• Excellent master's degree in artificial intelligence, robotics, data science or a related field
• Experience in developing and applying uncertainty-aware machine learning methods, particularly in the context of computer vision and autonomous systems
• Familiarity with techniques for uncertainty quantification, neural network monitoring, and robustness evaluation
• Excellent programming skills in Python
• Strong communication skills and the ability to work collaboratively in interdisciplinary teams

Autonomous driving? Unmanned flying? Digital production? The AI mobility hub Ingolstadt AImotion Bavaria is dedicated to this research focal points. Become part of the team and change the future of AI-based mobility with us! For more information, please visit https://www.thi.de/forschung/aimotion