About the job
NVIDIA Research is searching for a world-class new college grad PhD researcher to drive groundbreaking research at the intersection of AI HW/SW Co-Design, AI Hardware Accelerator Architecture, IC Design Methodology, and VLSI Design. Ideal candidates will have a perspective across areas including machine learning fundamentals, quantization and numerical methods for machine learning model optimization, digital VLSI circuits for computer arithmetic, high-productivity VLSI design and verification methodologies including applications of generative AI to hardware design, AI hardware micro-architecture, and VLSI methodology and implementation.
Responsibilities
AI Accelerator Hardware: Contribute to novel research advancing the state-of-the-art in AI accelerator design.
VLSI: Research creative and innovative ASIC and VLSI design techniques and/or novel digital VLSI circuits. Apply machine learning, generative AI, and innovative tools and methodologies to automated ASIC and VLSI design tool flows.
AI HW/SW Co-Design: Research and develop creative and innovative numerical methods for quantization, sparsity, or tensor decomposition grounded in computer arithmetic fundamentals and digital VLSI circuits.
Collaborate on the development of research prototype testchips.
Collaborate with AI researchers and hardware team members in research and product teams.
Publish and present your original research, speak at conferences and events
Qualifications
Minimum
PhD in Computer Science, Electrical/Computer Engineering, or related field (or equivalent experience)
VLSI Implementation Skills: Experience in hardware design with proficiency with modern EDA tool flows.
Programming & Systems Skills: Proficiency in at least two of Python, PyTorch, C++, SystemVerilog, or CUDA
Publications in top circuit, architecture, and/or AI/ML venues
Domain & Technical Expertise: PhD research experience in either VLSI (e.g., digital VLSI circuits and chip design methodologies), computer architecture, and/or numerical algorithms for AI model HW/SW co-design.
Excellent self-motivation, a high degree of creativity, and a passion for research, collaboration skills and the ability to work effectively within a research team.
Excellent written and verbal communication skills, with proven experience communicating technical work (e.g., academic presentations, poster sessions); ability to synthesize and explain complex technical concepts.
Preferred
No preferred qualifications listed.