Robotics Engineering Intern

Job description

Primary Function of Position The Robotics Engineering Intern will report to future forward research lad and contribute to creating a sim-to-real-to-sim platform for the Intuitive surgical robot system. The intern will enable rapid prototyping and de-risking of new controller architectures, particularly semi-supervised and supervised autonomous systems that are data-hungry and require extensive validation. Key functions include developing tools that systematically transfer and test controllers from simulation to robot hardware, building virtual models of the surgical field for simulation interaction, and closing the loop between simulation and reality to accelerate development and evaluation of autonomous controllers.

Essential Job Duties

Implement novel control architectures in high-level (e.g., MATLAB) and low-level (e.g., embedded C++) targets. Systematically test controller performance in simulation and on robot hardware. Create simulation environments that integrate constrained rigid-body dynamics (e.g., MuJoCo) and realistic texture and lighting (e.g., Isaac Sim). Synthesize simulated environments from video data, including geometry, texture, and inferred stiffness.

Execute closed-loop round-trip tests

train a controller in simulation, test it experimentally, and use experimental data to construct new simulation environments.

Qualifications

Required Skills and Experience

University Hiring Program Eligibility Requirements: University Enrollment: Must be currently enrolled in and returning to an accredited degree-seeking academic program after the internship.

Internship Work Period

Must be available to work full-time (approximately 40 hours per week) during a 10-12 week period starting May or June. Specific start dates are shared during the recruiting process. Required Education and Training Current enrollment in a Robotics, Electrical Engineering, Mechanical Engineering, Computer Science, or related degree-seeking program at the Master's or Doctorate level. Working Conditions None.

Preferred Skills and Experience

Experience with MATLAB and/or Python for control system design and analysis. Experience with MuJoCo or similar constrained rigid-body dynamics simulators. Experience with sim-to-real transfer methods for robotic systems. Familiarity with NVIDIA Isaac Sim or similar platforms for realistic rendering and simulation. Familiarity with embedded C++ for low-level controller implementation. Awareness of video-based 3D reconstruction and environment synthesis techniques.

Awareness of autonomous or semi-autonomous control architectures.