Your tasks
During this internship, you will explore advanced methods in E2E AI-based planning to address challenges in autonomous systems. A few of your responsibilities will include:
- Conduct advanced research and engineering in E2E AI-based planning to address challenges in autonomous systems
- Apply research results to real-world applications with high quality implementation.
- Integrate the resulting system/software into existing Bosch platform.
- Summarize research findings in high-quality paper and/or patent submissions.
Your profile
Basic Qualifications
- Currently enrolled and pursing a Masters or PhD program in Computer Science or related fields
- Hands-on experience on developing classical and learning-based planners with focus on at least two of the following areas: reinforcement learning (RL), curriculum learning, imitation learning, action chunking, hybrid A*, LQR.
- Solid understanding of autonomous driving architectures including mission-level and behavioral planning
- Solid Python and/or C++ programming skills and proficient with libraries such as OpenCV, Tensorflow, and PyTorch.
- Minimum GPA of 3.0
Preferred Qualifications
- Publication record in top venues including CVPR, ICCV, ICRA, ISMAR, ECCV, NeurIPS, ICLR, TVCG, SIGGRAPH.
- Experience in working with close-loop systems, path tracking and vehicle kinematics models
- Able to work independently, has strong research and problem-solving skills.
- Strong background in math and statistics.
- Good communication and teamwork skills.
