About The Position

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.

Requirements

  • 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

Nice To Haves

  • 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.

Responsibilities

  • 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.
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