Postdoctoral Scholar - SAF Lab, Compass

What you'll do

• Advance safe autonomy research, including control barrier functions, learning integration, and perception-based synthesis.
• Build simulation, evaluation, and sim-to-real pipelines; deploy and validate methods on physical robots.
• Publish research and collaborate with product teams and science leaders on a research roadmap.

What they ask for

• PhD in Computer Science, Robotics, Control, Mechanical Engineering, Electrical Engineering, or a related field focused on control, learning, and/or robotics.
• Deep understanding of safety-critical control, including control barrier functions and safety filters.
• Proficiency in C++ and Python, with experience implementing control algorithms and/or learning policies.
• Robotics physics-simulator experience, physical robot hardware validation, and a publication track record at top-tier control and robotics venues.

Nice to have

• Knowledge of locomotion, nonlinear and whole-body control, reachability, and layered control architectures.
• Experience with learning-based robotics, CBF synthesis, robotic perception, predictive control, or large-scale reinforcement learning infrastructure.

Pay

151,200.00 USD Annually (base salary)

Tools

C++, Python, Isaac Gym/Sim, MuJoCo, PyBullet

AI focus

Research safe autonomy involving safe reinforcement learning, integrating control barrier functions with learning, and synthesizing safety methods from perception; validate approaches in simulation and on robotic hardware.