NVIDIA 2027 Internships: Ph.D. Research Computer Architecture and Systems
NVIDIAJob Title
NVIDIA 2027 Internships: Ph.D. Research Computer Architecture and Systems
Role Summary
Ph.D. research internship within NVIDIA's Computer Architecture and Systems research teams. Interns will perform original research, build prototypes, and collaborate with product groups to transfer results into products or publications.
This role emphasizes research in GPU/CPU architectures, systems software, AI systems, and related areas supporting NVIDIA's computing and graphics platforms.
Experience Level
Entry-level — intended for current Ph.D. students. No specific years of post-degree work experience required beyond active Ph.D. enrollment.
Responsibilities
Intern responsibilities focus on research, prototyping, and collaboration to advance NVIDIA's architecture and systems capabilities.
- Design and implement novel ideas in GPU/CPU architecture, systems architecture, operating systems, AI systems, and distributed systems.
- Develop prototypes and experimental evaluations to validate research hypotheses.
- Collaborate with other researchers, engineering teams, and external partners.
- Transfer research outcomes to product teams; contribute to patents, product features, and publications.
- Document and present research results to both technical and non-technical audiences.
Requirements
Key technical and research qualifications for applicants. Degree details are listed under Education Requirements below.
- Must-have: Strong research record with publications at top conferences; excellent communication and collaboration skills.
- Must-have: Programming proficiency in C, C++, Python; familiarity with CUDA is often required depending on the project.
- Preferred: Prior research or development experience in one or more of the areas listed below.
- Preferred experience areas include: chip- and system-level architecture, GPU and multi-GPU architecture, scalable memory systems, interconnects, scheduling, power/performance/energy optimization, specialized accelerators, hardware-software co-design.
- Additional preferred areas: systems for AI/ML, infrastructure for large model training and inference, programming systems and compilers for parallel/GPU-accelerated computing, distributed runtime systems, high-performance networking and interconnects, VLSI and EDA (including GPU-accelerated EDA).
- Strong analytical skills and the ability to design experiments and analyze results.
Education Requirements
Must be actively enrolled in a Ph.D. program in Computer Science, Electrical Engineering, or a related field for the full duration of the internship; anticipated graduation month and year must be shown on the resume/CV. Enrollment and Ph.D. status are required; equivalent experience language not specified.
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.
