Research Associate (Robotics)
Core
Develop robust, intelligent navigation systems for inspection and humanoid robots, focusing on autonomous localization, decision-making, and motion planning in complex environments.
Role type
Research Associate (Robotics)
Builds
Navigation algorithms, motion planning modules, and learning-based policies for humanoid robots
Domain
Robotics, Autonomous Systems, Machine Learning
Deliverable
research
Required skills
robot motion planning and control, autonomous decision-making, robot localization and navigation, reinforcement learning, imitation learning, diffusion models, Python, C++, PyTorch, robotics physics simulators
Preferred skills
humanoid locomotion, whole-body control, trajectory optimization, model predictive control, generative decision-making
Responsibilities
Design and develop navigation algorithms for inspection robots; Work on global and local motion planning, obstacle avoidance, and trajectory tracking; Investigate diffusion models and reinforcement learning for navigation; Integrate visual navigation with humanoid locomotion; Build and evaluate algorithms in simulation and on real-world platforms; Contribute to publications and technical reports; Assist in mentoring students
Seniority
Mid-level, hands-on research
