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Applied Scientist, Safe RL, Robotics, SAF Lab

Pasadena, California, USA

USD 142K-193K Mid-level Full Time

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Found 5d ago
Tasks
Perks/Benefits
Skills/Tech-stack

Barrier functions | Constrained Markov Decision Process | Control barrier functions | Distributed Training | Domain Randomization | GPU Parallelization | Isaac Sim | Isaac-Gym | JAX | Lagrangian Methods | Latency optimization | Lyapunov Methods | Markov Decision Process | Model-Predictive Control | Mujoco | Operational Space | Operational Space Control | Physics simulation | Predictive control | PyBullet | PyTorch | Python | Python programming | Quadratic Programming | Real Time | Real-time Systems | Reinforcement Learning | Reinforcement Learning Training | Reinforcement Learning Training Pipelines | Reward shaping | Safe Reinforcement Learning | Safety filters | Shielding | Sim-to-Real | Sim-to-Real Transfer | Space Control | System Identification | Time Systems | Training pipelines | Whole-body control

Education

PhD

Roles

Applied Scientist | Scientist

Regions

North America

Countries

United States

States

California, US

Cities

Pasadena, California, US

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