Applied Research Intern

About the Role

NVIDIA is looking for a graduate research intern to advance integrated sensing and communications (ISAC) on NVIDIA GPU-accelerated platforms. The role involves joining a team building AI-native wireless systems and developing, training, and testing ISAC algorithms end-to-end on the NVIDIA Aerial Testbed. This position is suitable for a student interested in both deep algorithm work and practical system implementation.

Key Responsibilities

• Develop, implement, and benchmark ISAC algorithms in Python on NVIDIA GPU platforms.
• Build radar signal processing pipelines, including radar cube formation, range and Doppler processing, angle estimation, CFAR detection, and clutter suppression (e.g., MTI, static clutter removal, adaptive filtering).
• Compose new ML model architectures for sensing and joint sensing-communications tasks.
• Formulate corresponding loss functions and optimization objectives.
• Train and evaluate models in PyTorch using simulated and over-the-air captured data.
• Integrate algorithms with the NVIDIA Aerial Testbed and run real-time, over-the-air experiments.
• Document results and contribute to publications, patents, and internal technical reports.

Requirements & Tech Stack

• Currently enrolled in an MS or PhD program in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• Strong background in AI/ML for wireless communications.
• Solid understanding of ISAC concepts and waveforms (e.g., OFDM-based sensing).
• Hands-on experience implementing ISAC or radar algorithms in Python.
• Hands-on experience with PyTorch or another machine learning framework (e.g., TensorFlow, JAX).
• Demonstrated ability to build new ML model architectures and formulate optimization and loss functions.
• Knowledge of the signal processing aspects of ISAC, including radar cube algorithms and clutter reduction techniques.
• Strong communication skills and ability to work in a collaborative research team.

Ways To Stand Out From The Crowd

• PhD candidate with publications in ISAC, radar, or ML for wireless.
• Hands-on experience with real-time over-the-air wireless testbeds (e.g., software-defined radios like USRP, or 5G testbeds).
• Experience with GPU programming or acceleration (e.g., CUDA, CuPy).
• Familiarity with NVIDIA Aerial (CUDA-Accelerated RAN, Aerial Omniverse Digital Twin) or NVIDIA Sionna.
• Knowledge of the 3GPP 5G NR physical layer and 6G ISAC study items.