PhD Research Intern - Electronic Design Automation (2027)
NVIDIAJob Title
PhD Research Intern - Electronic Design Automation (2027)
Role Summary
NVIDIA Research seeks PhD students for a research internship applying AI and GPU acceleration to electronic design automation (EDA). The role focuses on researching and developing GPU-accelerated optimization and EDA algorithms, formal methods, agentic AI, and reinforcement learning techniques for chip-design workflows.
Interns will collaborate with circuits, VLSI, and architecture teams and are expected to plan, publish, and present original research.
Experience Level
Internship - for current PhD students (research-focused role).
Responsibilities
Typical responsibilities for this research internship include:
- Apply AI (agentic AI, LLMs, generative AI, reinforcement learning) and GPU acceleration to chip-design workflows.
- Research and develop novel EDA software and algorithms (optimization, physical design, formal methods, timing/signoff).
- Prototype and implement research code and experiments (rapid prototyping in Python; production code in C++/CUDA where applicable).
- Collaborate with circuits, VLSI, and architecture researchers and product teams.
- Prepare and submit research publications and present results at conferences and internal forums.
Requirements
Key qualifications and skills. Degree requirement is listed separately under Education Requirements.
- Must-have: Publications in leading EDA or AI conferences demonstrating AI-for-EDA, formal methods, or GPU-accelerated EDA research.
- Must-have: Strong programming and rapid-prototyping ability (Python); ability to implement and evaluate research code.
- Must-have: Demonstrated expertise with EDA algorithms (formal verification, logic synthesis, physical design, timing and signoff) and experience applying AI methods to practical EDA problems.
- Must-have: Strong written and verbal communication skills; experience presenting technical work (papers, posters, talks).
- Nice-to-have: C++, parallel programming experience (CUDA), reinforcement learning, GPU programming, or agentic AI experience.
Education Requirements
Pursuing a PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related technical field; enrollment as a current PhD student is required. The posting expects a record of research output (publications) in relevant conferences.
About the Company
Company: NVIDIA
Headquarters: Santa Clara, California, USA
NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.
