D. preferred) in Aerospace, Mechanical, Electrical, Robotics, Computer Science, Computational Science, or related field- Hands-on experience with NVIDIA Isaac Sim / Isaac Lab for robotics scenario simulation (locomotion, manipulation, repeatable environments, terrain/contact interaction, domain randomization, logging/analysis)- Experience with MuJoCo, Drake, or Gazebo for dynamics modeling, RL policy training, or hardware-in-the-loop workflows- Experience with ROS 2 / MoveIt 2 integration for manipulation planning and sim-to-real deployment- Sim-to-real transfer experience: domain randomization, system identification, reality gap characterization- Reinforcement learning or learning-based control applied to locomotion or manipulation tasks- Lunar or planetary surface terra mechanics experience (slip/traction modeling, sinkage/rolling resistance, slope handling)- MIL/SIL/HIL verification experience and automated regression testing of simulation scenarios- Experience correlating models to hardware test data (system identification, parameter estimation, model credibility frameworks)- Experience applying modern software practices to modeling/simulation (CI/CD, automated tests, configuration/parameter management, containerized environments). - Stand up and iterate dynamic models to evaluate system concepts, margins, and operational envelopes for locomotion and manipulation systems- Build scenario-based simulation studies — wheeled/legged mobility, robotic manipulation — using physics engines (NVIDIA Isaac Sim, MuJoCo, Gazebo, Drake, or equivalent) to inform requirements and design decisions- Develop contact and terra mechanics approaches at appropriate fidelity levels; quantify key sensitivities and uncertainties- Provide simulation data products (control margins, sensitivity sweeps, operational envelopes) to support control architecture and actuator trades- Produce model maturation plans, test-to-model correlation plans, and phased verification strategies (MIL SIL HIL)- Generate synthetic data and simulation-based datasets to support ML, reinforcement learning, and sim-to-real transfer.