NVIDIA 2027 Internships: Ph.D. Research Computer Architecture and Systems
About The Position
NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society — from gaming to robotics, self-driving cars to life-saving healthcare, climate change to virtual worlds where we can all connect and create. Our internships offer an excellent opportunity to expand your career and get hands on experience with one of our industry leading Computer Architecture and Systems teams. We’re seeking strategic, ambitious, hard-working, collaborative, and creative individuals who are passionate about helping us tackle challenges no one else can solve.
Requirements
- Must be actively enrolled in a university pursuing a Ph.D. degree in Computer Science, Electrical Engineering, or a related field, for the full duration of the internship; anticipated graduation date (month and year) must be clearly indicated on a resume or CV to be considered.
- Depending on the internship, prior experience or knowledge requirements could include the following programming skills and technologies: C, C++, Python, CUDA.
- Strong background in research with publications at top conferences.
- Excellent communication and collaboration skills.
- Potential internships require research experience in at least one of the following areas: Chip-level and System-level Architecture, GPU and Multi-GPU Architecture, Scalable memory systems and new memory technologies, Scalable on-chip and off-chip interconnects, Chip-level and system-level scheduling, Power, performance, and energy-efficiency in large-scale systems, Specialized accelerators for workloads like AI algorithms, crypto algorithms, databases, etc., Hardware-software co-design, Systems for AI/ML, Systems Infrastructure for large LLM training and inference, Systems/AI algorithms codesign (e.g., for sparsity), AI/ML for systems (hardware design, code optimization, etc.), ML for EDA, Programming Systems, GPU-accelerated algorithms, Languages and programming models for parallel computing, Optimizing compilers and AI-based performance assistants, Distributed runtime systems, Systems software and operating system interfaces, Optimizing GPU-accelerated workloads, Compilers and code verification, High-Performance Networking and Interconnects, Large-scale GPU networking, Topologies, routing, and congestion control, Networking techniques at the intersection of scale-out and scale-up, VLSI and Electronic Design Automation (EDA), GPU Accelerated EDA.
Responsibilities
- Design and implement novel ideas in GPU and CPU architectures, systems architectures, operating systems, AI systems, and distributed systems that advance computing, graphics, media processing, and related technologies central to NVIDIA's business.
- Collaborate with other team members, teams, and/or external researchers.
- Transfer your research to product groups to enable new products or types of products.
- Deliverable results include prototypes, patents, products, and/or publishing original research.
Benefits
- Intern benefits
- Internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Intern
Education Level
Ph.D. or professional degree
