VLSI Timing Methodology Intern - Summer 2027

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to resolve, that only we can seek, and that matter to the world. This is our life’s work, to amplify human inventiveness and intelligence. If you enjoy combining multiple interests across VLSI design, device modeling, Static timing Analysis, software development, accelerated computing and AI, you’ll love the kind of work we do. Our team combines advances in both high-performance software and VLSI hardware design to craft large scale internal CAD tools and silicon projection methodologies for delivering outstanding computing hardware. If you are passionate about innovation in these areas, let’s talk about many possible projects. What you’ll be doing: Research and develop compact device and system models to predict silicon, both time-0 and aged, timing behavior in pre-silicon simulation world Use Machine Learning and analytical techniques to speed up device and system timing characterization. Develop tools, and methodologies to predict and improve silicon performance and reliability beyond what industry standard tools can offer alone. Explore how physical effects (e.g., IR drop, crosstalk, aging, thermal impact) influence timing and design decisions.