To achieve this, we are seeking highly motivated interns to support our research team on the topic of uncertainty estimation for end-to-end (E2E) autonomous driving within our Perception Team in Sindelfingen. Compared to modular pipelines that separately process perception, prediction and planning, E2E models jointly optimize all stages within a single framework, resulting in simpler architectures and reduced information loss across modules. We look forward to receiving your online application, including a resume, cover letter, certificates, current certificate of enrollment stating your semester, proof of mandatory internship if applicable, and proof of the standard period of study. * Solid foundation and in-depth understanding of deep learning techniques, especially neural networks, and common software frameworks (e.g., PyTorch, MMDetection family)
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