Postdoc in Learning-Based Constrained Motion Planning (Robotics, AI, Optimization) at Universidad Pontificia Comillas

The TRAIL Lab at Universidad Pontificia Comillas, led by Assistant Professor Jesús Tordesillas Torres, is seeking a Postdoctoral Researcher in the area of learning-based constrained motion planning. The position focuses on developing advanced methods for trajectory planning under constraints such as safety, feasibility, and system dynamics, leveraging artificial intelligence, robotics, and optimization techniques. The lab's research spans topics including multiagent and dynamic environments, perception-aware planning, differentiable simulation for locomotion, and constraint guarantees on neural networks. Applicants should have a PhD in Robotics, Machine Learning, Control, Computer Science, or a closely related field. Essential qualifications include hands-on experience with trajectory planning and/or optimization, as well as advanced programming proficiency in Python or C++. The TRAIL Lab is known for its contributions to decentralized and asynchronous multiagent trajectory planning, differentiable simulation, and robust navigation in challenging environments. The group collaborates with leading institutions such as MIT and ETH Zürich, and has a strong publication record in top robotics conferences and journals. While the post does not specify funding details, interested candidates are encouraged to contact Prof. Tordesillas directly for information regarding salary, benefits, and funding arrangements. The application process is straightforward: send your CV to [email protected]. For more information about the lab's research and ongoing projects, visit the TRAIL Lab website. This is an excellent opportunity for researchers interested in robotics, AI, and optimization to join a dynamic and innovative team in Spain.