# Robotics Intern **Company**: NVIDIA **Job type**: internship **Category**: Engineering **Industry**: Technology **Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/Switzerland-Zurich/Robotics-Simulation-and-Evaluation-PhD-Intern---Summer-2027_JR2027531?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply **Canonical**: https://yubhub.co/jobs/job_e087a4b4-d14 ## Description NVIDIA is seeking dedicated interns to join our robotics team. You will develop novel approaches to agentic robot policies, world action models, robot policy training and evaluation, and sim-to-real transfer, working alongside researchers and engineers who build NVIDIA's robotics and simulation platforms. **Responsibilities** - Work closely with experts in robotics and machine learning to scope a challenging project that is both scientifically novel and relevant to NVIDIA's robotics roadmap. - Design, implement, and evaluate new robot learning methods using GPU-accelerated simulation and, where appropriate, real robot hardware. - Run rigorous experiments: build strong baselines, design evaluation protocols, ablate your ideas, and communicate clearly. - Write clean, well-documented research code that other team members can build on. - Collaborate with researchers and internal product teams to transfer your research into NVIDIA products and platforms. - Deliver results as prototypes, patents, product contributions, and publications at top-tier venues. **Requirements** - Currently enrolled in a Ph.D. program in Computer Science, Electrical Engineering, Robotics, or a related field. - Research experience in one or more of the following: agentic policies, world action models, robot policy training and evaluation, or sim-to-real transfer, demonstrated through publications, preprints, a thesis, or open-source projects. - Strong Python skills and hands-on development experience with a modern deep learning framework (e.g., PyTorch, JAX). - Strong written and verbal communication skills, including presenting research results to both experts and non-experts. **Nice to Have** - First-author publications at top robotics and machine learning venues (e.g., CoRL, RSS, ICRA, IROS, NeurIPS, ICML, ICLR, CVPR). - Deep expertise in robot learning: reinforcement learning, imitation learning, or training and fine-tuning large vision-language-action (VLA) or world models for robotics. - Deep expertise in GPU-accelerated physics simulation (e.g., PhysX, Isaac Gym / Isaac Lab, Newton, MJX), including building simulation environments, assets, or domain randomization pipelines. - Experience deploying learned policies on real robot hardware (manipulators, humanoids, or mobile robots) and closing the sim-to-real gap. - Experience with large-scale, multi-GPU training and data pipelines with contributions to open-source robotics or simulation projects. ## Skills ### Required - Python - deep learning frameworks (PyTorch, JAX) - robotics - machine learning ### Nice to have - reinforcement learning - imitation learning - GPU-accelerated physics simulation - robot learning --- Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/Switzerland-Zurich/Robotics-Simulation-and-Evaluation-PhD-Intern---Summer-2027_JR2027531?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)