PhD Research Intern: GPU Architecture & Systems

NVIDIA Corporation; Santa Clara (CA); On-site; USD 52,000 - 129,000; Full time

Benefits offered by this job

Intern benefits

Competitive hourly rate

Job summary

NVIDIA Corporation invites a PhD candidate to join the Architecture Research Group as an intern focused on defining the future of GPU and data-center computing. You will work across hardware and software boundaries, building models, simulators, prototypes, and tools to evaluate architectural ideas and co-design opportunities with researchers and product teams.

Ideal candidates have a strong foundation in computer architecture, parallel systems, and experience with CUDA, CPUs/GPUs programming,

Qualifications

• Pursuing PhD in CS/CE/EE/Physics/Math.
• Strong C/C++ and scripting skills.
• Experience with CUDA programming.
• Experience building computer system simulators.
• Experience building low-level software tools like runtime systems, binary translators or compilers.

Responsibilities

• Investigate new architecture concepts for future GPUs, memory systems, accelerators, and data-center-scale platforms.
• Study emerging workloads to identify bottlenecks and opportunities.
• Explore hardware-software co-design across architecture, compilers, and runtimes.
• Develop models, simulators, prototypes, and experimental tools to evaluate ideas.
• Communicate research findings through presentations, reports, and publications.
• Transfer successful research ideas and tools into NVIDIA product teams.

Skills

C/C++ programming

CUDA programming

Scripting languages

Parallel computing

Computer architecture

Education

Pursuing PhD in CS/CE/EE/Physics/Math

Tools

Computer system simulators

Runtime systems

Binary translators

Compilers

Job description

NVIDIA Corporation invites a PhD candidate to join the Architecture Research Group as an intern focused on defining the future of GPU and data-center computing. You will work across hardware and software boundaries, building models, simulators, prototypes, and tools to evaluate architectural ideas and co-design opportunities with researchers and product teams.

Ideal candidates have a strong foundation in computer architecture, parallel systems, and experience with CUDA, CPUs/GPUs programming,