Motion Planning Engineer (PhD, Intern)

<p style="line-height: 1.3;"><strong>About The Company</strong></p> <p style="line-height: 1.3;">DiDi's autonomous driving unit was established in 2016 with the mission of developing Level 4 autonomous driving (AD) technology to make transportation safer and more efficient. In August 2019, the unit became an independent company, DiDi Autonomous Driving, dedicated to advanced AD R&amp;D, product application, and business expansion. We believe integrating AD technology into a shared-mobility fleet will generate immense social value. By leveraging DiDi's specialized technology, operational expertise, and integrated ecosystem, we are positioned to build and operate a highly efficient, user-oriented autonomous fleet.</p> <p style="line-height: 1.3;"><br><strong>About The Role</strong></p> <p style="line-height: 1.3;">We are seeking a motivated PhD graduate with a strong research background in motion planning, robotics, or autonomous systems. In this role, you will apply your expertise in algorithm design and system integration to help develop next-generation planning capabilities for autonomous vehicles.<br><br></p> <p style="line-height: 1.3;"><strong>Responsibilities<br></strong></p> <ul> <li>Implement novel solutions for Behavioral Planning, enabling high-level decision-making for lane changes, merges, yields, and multi-agent interactions.</li> <li>Design and optimize motion planning algorithms that integrate geometry-based path reasoning and context-aware speed reasoning into smooth, safe trajectories.</li> <li>Develop and improve core geometry and velocity planning systems to ensure feasibility, compliance, and comfort across diverse driving scenarios.</li> <li>Model complex driving environments and agent behaviors to create a robust world representation for planning under uncertainty.</li> <li>Formulate cost functions and optimization frameworks that balance safety, comfort, and efficiency in trajectory selection.</li> <li>Analyze, test, and debug system performance through simulation and real-world data, conducting root-cause investigations and proposing enhancements.</li> <li>Collaborate with researchers and engineers across Perception, Prediction, and Control to ensure an integrated, reliable autonomy stack.<br><br></li> </ul> <p style="line-height: 1.3;"><strong>Qualifications<br></strong></p> <ul> <li>Recently completed or soon-to-complete PhD in Robotics, Computer Science, Electrical Engineering, or a related field.</li> <li>Research or Internship experience in one or more of the following:</li> <li>Motion planning algorithms (optimization, sampling, graph/search-based methods)<