Doctoral Candidate (m/f/d) Computer Vision for Autonomous Driving

Your tasks:

• 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

Your profile:

• Excellent masters 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

Contact ANR 1879 please feel free to contact Milena Porsch

• 49 841 9348-5062

We look forward to you!

What we offer: excellent labratory equipment innovative working environment collaboration with industry partners comprehensive support & guidance future oriented learning opportunities doctorate in engineering and information science homeoffice & mobile working flexible working hours canteen & restaurant Good connections & central location Short info Contract 40 h/week Duration until 31.12.2030 Payment TV-L EG 13 Location Ingolstadt Application until 22.10.2025 Good to know

In general, our positions are available on a part-time basis. Severely disabled applicants are given preferential consideration in the event of equal qualification. We are striven to increase the number of employed women and therefore particularly welcoming towards applications from women (Article 7(3) BayGIG).