PhD Research Intern, AI for Climate and Weather Simulation - 2027
$0k - $0k • Remote • US, CA, Santa Clara
Posted 1d ago
Remote Work Policy
Fully remote
Categories
AI Research Engineer
About the job
NVIDIA is seeking research interns with a strong background in applying modern AI methods to re-imagine technology across Earth System Simulation and Analytics. This role involves research on applied topics such as 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. We are looking for creative, independent, and self-starting individuals to help invent the future of AI in climate science. The ideal candidate will have strong computer science skills with knowledge of physical domain sciences, or strong domain science skills with sufficient technical expertise. Join a diverse research group that tackles challenging interdisciplinary problems, publishes at top venues, and drives real impact on NVIDIA products and global climate prediction.
Responsibilities
- Propose, research, prototype, and test innovative research ideas.
- Publish groundbreaking work at top conferences and journals.
- Collaborate with research team members, interns, product teams, and external researchers.
- Contribute to technology transfer by working with engineers as research transitions to product.
- Utilize NVIDIA GPUs for cutting-edge research at the intersection of AI and climate science.
Requirements
- Currently enrolled in at least the 2nd year of a Ph.D. in geophysical sciences, computer science, applied math/statistics, or related fields.
- Strong research portfolio including one first-author publication that utilizes AI.
- Proficiency or demonstrable ability to quickly learn distributed deep learning training frameworks like PyTorch.
- Strong software engineering skills, including PyTorch, PyTorch-lightning, shell scripting, software environment management, and high-performance parallel GPU computing.
- Experience in scaling algorithms for high computational loads is a plus.
- Experience developing in a changing software environment and ability to drive research projects end-to-end is a plus.
- Expertise in climate domain science, nonlinear physics, or deep familiarity with associated datasets and/or physical simulation systems is a plus.
- Excellent communication skills.
Benefits
- Internship hourly rates
- Intern benefits