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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # NVIDIA 2027 Internships: Ph.D. Research Computer Architecture and Systems - **Company:** NVIDIA Ltd. - **Location:** Santa Clara, CA, United States - **Salary:** $79,040.0 - $195,520.0 - **Contract:** Internship / Graduate position - **Skills:** C (Programming Language), Artificial Intelligence, Very-Large-Scale Integration, C++ (Programming Language), Compilers, Program Optimization, Nvidia CUDA, Computer Programming, Databases, Network Congestion, Distributed Systems, Electronic Design Automation, Hardware Design, Python (Programming Language), Routing, Software Engineering, Systems Architecture, Graphics Processing Unit (GPU), Large Language Models, Parallel Computation, Information Technology - **Published:** August 20, 2026 - **Apply:** https://www.disabledperson.com/jobs/74390849-nvidia-2027-internships-ph-d-research-computer-architecture-and-systems ## About the Role * 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) ## Description * 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. ## Related Videos - [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia) - [Creating a routing app with Google Maps API from scratch](https://www.wearedevelopers.com/videos/831-creating-a-routing-app-with-google-maps-api-from-scratch) - [Just-in-time Compilation in JVM](https://www.wearedevelopers.com/videos/240-just-in-time-compilation-in-jvm) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [Accelerating Python on GPUs](https://www.wearedevelopers.com/videos/859-accelerating-python-on-gpus) ## Related Articles - [Top 6 Hackathons for Developers in 2023](https://www.wearedevelopers.com/magazine/263-top-6-hackathons-for-developers-in-2023) - [Steps to Get a Software Engineer Internship](https://www.wearedevelopers.com/magazine/160-steps-to-get-a-software-engineer-internship) - [What’s the latest in NVIDIA CUDA Python](https://www.wearedevelopers.com/magazine/568-what-s-the-latest-in-nvidia-cuda-python) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [The Fastest-Growing Tech Sectors to Look Out for in 2025](https://www.wearedevelopers.com/magazine/373-the-fastest-growing-tech-sectors-to-look-out-for-in-2025)