PhD Research Intern — Autonomous Systems & Physical AI

NVIDIA Gruppe; Santa Clara (CA); Presencial; USD 52.000 - 129.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Intern benefits

Descripción de la vacante

NVIDIA's Autonomous Systems and Physical AI Research (ASPIRE) invites outstanding Research Interns to explore perception, robotics, and safe interaction in real-world environments. You will work on autonomous vehicles, robotics, and physical AI challenges, with opportunities to publish and open-source code.

As part of a diverse, interdisciplinary team, you will design and implement cutting-edge techniques, run experiments, report results, and transfer findings to product groups.

Formación

• Pursuing a PhD in Robotics, Computer Science, Computer Engineering, or a related field.
• Strong research experience in autonomous vehicles, robotics, embodied AI, or autonomous systems.
• Excellent programming skills in Python; experience with C++ and parallel computing (CUDA) is a plus.

Responsabilidades

• Designing and implementing cutting-edge techniques for autonomous vehicles, robotics, and physical AI.
• Conducting original research and publishing your results.
• Collaborating with research colleagues, internal product teams, and external researchers.
• Transferring technology you've developed to relevant product groups.

Conocimientos

Python programming

Research experience

C++

Communication skills

Problem solving

Educación

PhD in Robotics, Computer Science, Computer Engineering, or related field

Herramientas

CUDA

PyTorch

Descripción del empleo

NVIDIA's Autonomous Systems and Physical AI Research (ASPIRE) invites outstanding Research Interns to explore perception, robotics, and safe interaction in real-world environments. You will work on autonomous vehicles, robotics, and physical AI challenges, with opportunities to publish and open-source code.

As part of a diverse, interdisciplinary team, you will design and implement cutting-edge techniques, run experiments, report results, and transfer findings to product groups.