[Skip to main content](#main-content) [OpenNash Jobs](https://jobs.opennash.com/) [Hiring report](/reports/hiring/) · [All NVIDIA jobs](https://jobs.opennash.com/companies/nvidia/) · [Search jobs](/search/) NVIDIA · Santa Clara, CA # Differentiable Simulation Research Intern - Summer 2027 US, CA, Santa Clara Early career Research & Science Listed on NVIDIA’s official careers site. Posted October 13, 2026. Check that it is still open and apply there. [Apply on NVIDIA’s careers site →](https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Differentiable-Simulation-Research-Intern---Summer-2027_JR2027561) [OpenNash Jobs](https://jobs.opennash.com/) / [NVIDIA](https://jobs.opennash.com/companies/nvidia/) / Differentiable Simulation Research Intern - Summer 2027 ## Job description Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in an inclusive, encouraging environment where everyone is inspired to do their best work. Come join the team and see how we can make a lasting impact on the world. Research in this internship will focus on scalable differentiable algorithms, including adjoint and automatic differentiation methods. The work will connect simulations with experimental data for calibration and data assimilation using AI/ML methods. These approaches will be evaluated on simulation workloads and assessed for integration into NVIDIA software used by researchers, engineers, and partner developers. If you enjoy working across mathematics, code, hardware, and engineering applications, we would love to meet! ### What you'll be doing Prototype GPU-native solvers with adjoint and automatic differentiation techniques for engineering simulations. Integrate AI-based methods with simulation algorithms for parameter calibration, inverse problems, and data assimilation using experimental or simulation data. Co-design numerical algorithms and differentiation strategies for GPU parallelism, memory hierarchy, mixed precision, reduced synchronization, and distributed multi-GPU execution. Evaluate numerical accuracy, convergence, gradient quality, performance, and scalability on workloads in CFD, mechanics, thermal systems, and multiphysics. Identify promising methods and help move them toward reusable capabilities in CUDA-X libraries. ### What we need to see Pursuing a PhD in applied mathematics, scientific computing, computational engineering, computer science, mechanical engineering, aerospace engineering, or equivalent program area. Strong foundations in algorithms related to PDEs, numerical linear algebra, iterative solvers, optimization, or scientific computing. Research experience with adjoint methods, automatic differentiation, inverse problems, data assimilation, gradient-aware simulation approaches, or a related area. Experience writing numerical software in Python and C++, with familiarity with parallel or GPU computing. Ability to design computational experiments, evaluate numerical and performance tradeoffs, and communicate technical results clearly. ### Ways to stand out from the crowd Experience developing, scaling, or analyzing GPU solvers, including multi-GPU or distributed execution. Hands-on CUDA experience and use of profiling, benchmarking, or performance analysis to improve numerical algorithms. Experience calibrating computational models or assimilating experimental data in scientific or industrial applications. Experience with NVIDIA Warp, CUDA-X libraries, PyTorch, JAX, PETSc, Trilinos, MFEM, libCEED, OpenFOAM, or related computational science frameworks. Publications, open-source contributions, or deployed research software in numerical methods, scientific computing, differentiable simulation, or computational engineering. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! 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 - 94 USD. You will also be eligible for Intern benefits. ​ Applications for this job will be accepted at least until October 16, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. ## At a glance - Posted by the employer: Oct 13, 2026 - First seen by OpenNash: Oct 13, 2026 - Last checked: Oct 20, 2026 - Listed for: 7 days - Location: US, CA, Santa Clara[Apply on NVIDIA’s careers site →](https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Differentiable-Simulation-Research-Intern---Summer-2027_JR2027561) ## More jobs at NVIDIA ### [Applied Deep Learning PhD Research Intern, Reinforcement Learning for LLMs - Fall 2026](https://jobs.opennash.com/companies/nvidia/jobs/42d001528f77c6d200c8/) US, CA, Santa Clara ### [Offensive Hardware Security Researcher](https://jobs.opennash.com/companies/nvidia/jobs/a71034a3f826a4b2b81a/) US, CA, Santa Clara ### [PhD Research Intern, AI-Aided Engineering – 2027](https://jobs.opennash.com/companies/nvidia/jobs/b8bae8c21e6005c2f768/) US, CA, Santa Clara ### [PhD Research Intern, Autonomous Systems and Physical AI Research - 2027](https://jobs.opennash.com/companies/nvidia/jobs/3e4b5a7d8d7c36938c02/) US, CA, Santa Clara ### [PhD Research Intern, Fundamental Generative AI - 2027](https://jobs.opennash.com/companies/nvidia/jobs/1ba8e1706ed337b2b822/) US, CA, Santa Clara ## Similar jobs at other companies ### [Summer 2027 - IEF - Flight/System Simulation Engineer Collegiate Associate Intern](https://jobs.opennash.com/companies/general-dynamics/jobs/cb31377ad1cdab6bc058/) General Dynamics · Savannah, GA, US ### [2027 Summer Intern - Research and Development - Defense Lab Modeling and Simulation](https://jobs.opennash.com/companies/general-motors/jobs/f4903218d4338c4d6202/) General Motors · Warren, Michigan, United States of America ### [2027 Summer Intern – Research and Developement – Display Optical Simulation](https://jobs.opennash.com/companies/general-motors/jobs/f84331e1a3daed5dac1c/) General Motors · Warren, Michigan, United States of America ### [Market Research & Analysis Intern - Summer 2027](https://jobs.opennash.com/companies/abb/jobs/e2b4730ac5f12818001b/) ABB · Cary, North Carolina, United States of America ### [Summer 2027 AIM Hedging Research Analyst Internship | Fully Onsite](https://jobs.opennash.com/companies/allianz/jobs/69e0ec28b8a1ca79b8d9/) Allianz · Minneapolis, Minnesota, United States [Jobs in Santa Clara, CA](/locations/us/ca/santa-clara/)[Jobs in California](/locations/us-ca/)[Research & Science jobs](/functions/research-science/) OpenNash lists jobs from employers’ own careers sites and does not handle applications. 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