Role Purpose & Objective :
- Develop and implement physics-based simulations and digital twin models for robotics systems.
- Design and validate control, motion planning, and machine learning algorithms in simulated environments.
- Ensure high-fidelity simulation validation and optimization for robotics platforms.
- Collaborate with cross-functional teams including hardware, software, and research groups to integrate simulation models.
Key Responsibilities :
Build and maintain robotics kinematics, dynamics, and control models.Develop simulation environments using tools like Isaac Sim, Mujoco, PyBullet, Gazebo, and PhysX.Implement and test motion planning, control, and ML algorithms within simulations.Optimize simulations for accuracy, performance, and real-world fidelity.Work with cross-functional teams to integrate CAD models, codebases, and real-world data into digital twins.Document simulation results, methodologies, and validation processes.Required Skills & Competencies :
Technical Skills :
Strong understanding of robotics kinematics, dynamics, and controls.Proficiency in Python and C++ for simulation and control development.Experience with robotics simulation tools : Isaac Sim, Mujoco, PyBullet, Gazebo, PhysX.Familiarity with CAD tools and version control systems (Git).Knowledge of control algorithms, motion planning, and machine learning for robotics.Behavioral Skills :
Strong analytical and problem-solving skills.Ability to collaborate across cross-functional teams.Detail-oriented with a focus on simulation accuracy and validation.Adaptability to work in a fast-paced research or development environment.Education :
BSc / MSc in Robotics or related field (mandatory)MSc / PhD with specialization in robotics simulation, digital twins, or physics-based modelingExpertise in digital twin development and simulation optimizationHands-on experience with Isaac Sim and physics-based modelingExperience Required :
3+ years in robotics simulation or related fields(ref : hirist.tech)