The ideal candidate for this research scientist position should be a Ph.D. student in EE or related field with a strong research record, well-referenced publications and/or patents. They should have a solid background in EDA algorithms and software development, machine learning, VLSI, circuits, IC design, and computer micro-architecture. Proficiency in C, C++, Python, and scripting languages, as well as experience with machine learning frameworks like PyTorch and Tensorflow, CUDA, and GPU computing is necessary. Additionally, excellent communication skills and dynamic presentation abilities are highly valued.

The candidate will be responsible for applying machine learning and GPU acceleration to EDA software and developing innovative algorithms, collaborating with various teams, publishing research, and collaborating with external researchers.

Research & Development

Data

United States

San Francisco

Austin

Large

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.

Manufacturing & Electronics

NVIDIA

<ul><li><br></li><li>NVIDIA’s 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 — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company, and build our teams with the smartest people in the world. Would you like to join us at the forefront of technological advancement?</li><li>NVIDIA Research is seeking leading researchers in the areas of VLSI electronic design automation (EDA) to contribute to the development of future high-performance and mobile computing systems. You should have a strong track record of research excellence; systems-building experience; a broad perspective across areas including EDA algorithms and software, machine learning, and VLSI chip design methodology. Specific areas of research interest include but are not limited to applications of supervised learning, unsupervised learning, reinforcement learning and GPU acceleration to EDA algorithms.</li></ul>

Currently Studying

NVIDIA’s 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 — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company, and build our teams with the smartest people in the world. Would you like to join us at the forefront of technological advancement?NVIDIA Research is seeking leading researchers in the areas of VLSI electronic design automation (EDA) to contribute to the development of future high-performance and mobile computing systems. You should have a strong track record of research excellence; systems-building experience; a broad perspective across areas including EDA algorithms and software, machine learning, and VLSI chip design methodology. Specific areas of research interest include but are not limited to applications of supervised learning, unsupervised learning, reinforcement learning and GPU acceleration to EDA algorithms.

Research Scientist, Design Automation - New College Grad 2024

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