Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 6
Algorithms @ 1
Communication @ 3
Deep Learning @ 5
GPU @ 6
Mathematics @ 3
PyTorch @ 5
Statistics @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA is seeking research interns with a strong background in applying modern AI methods across the Earth System Simulation and Analytics stack. Research topics may include generative data assimilation, hybrid climate simulation, full-model emulation of climate model components, regional-to-global high-resolution AI autoregressive weather prediction, and dynamical downscaling.
The role is suited to highly creative, independent, and self-starting researchers. Strong computer scientists with sufficient knowledge of physical domain sciences, as well as strong domain scientists with sufficient technical skills, are encouraged to apply. The research group works on interdisciplinary problems at the intersection of climate science and artificial intelligence, publishes at top venues, and contributes to NVIDIA products and the broader academic and government climate-prediction ecosystem.
Responsibilities
- Propose, research, prototype, and test innovative research ideas.
- Publish research at leading conferences and journals.
- Collaborate with research team members, fellow interns, internal product teams, and external researchers while receiving mentorship.
- Contribute to technology transfer with NVIDIA engineers as research ideas progress toward products.
- Use NVIDIA GPUs at scale for research in AI and climate science.
Requirements
- Currently enrolled in at least the second year of a PhD program in geophysical sciences, computer science, applied mathematics, statistics, or a related field.
- A strong research portfolio, including at least one first-author publication that makes effective use of AI.
- Proficiency in, or demonstrable ability to quickly learn, distributed deep learning training frameworks such as PyTorch.
- Strong software engineering skills, including PyTorch, PyTorch Lightning, shell scripting, software environment management, and high-performance parallel GPU computing.
- Experience scaling algorithms for high computational loads is a plus.
- Experience developing in changing software environments and the ability to drive research projects end-to-end are a plus.
- Expertise in climate domain science, nonlinear physics, associated synthetic or observational datasets, or physical simulation systems is a plus.
- Excellent communication skills.
Benefits
Interns are eligible for NVIDIA intern benefits.
The application deadline is at least October 25, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is committed to an inclusive, equal-opportunity work environment.