NVIDIA 2027 Internships: Ph.D. Research Computer Architecture and Systems

By submitting your resume, you acknowledge that your Ph.D. Research Computer Architecture and Systems internship application will be processed in accordance with NVIDIA’s Applicant Privacy Policy and you agree to our Terms of Service . We’ll review resumes on an ongoing basis, and a recruiter may reach out if your experience fits one of our many internship opportunities.  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.   Learn more about   Research at NVIDIA .

Design and implement novel ideas in GPU and CPU a rchitectures, 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.   What we need to see:   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   S ystems 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   Click   here   to learn more about NVIDIA, our early talent programs, benefits offered to students   and other helpful student resources related to our latest technologies and endeavors.   Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 38 USD -