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About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
1623 open roles
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Listed pay typically runs
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PhD Research Intern, AI for Climate and Weather Simulation - 2027 is a research internship within a diverse group focused on interdisciplinary problems at the intersection of AI and climate science. The intern will propose, research, prototype, and test innovative ideas to re-imagine the Earth System Simulation and Analytics stack. Key responsibilities include publishing groundbreaking work at top venues, collaborating with internal product teams, and contributing to technology transfer. Candidates must demonstrate proficiency in PyTorch, PyTorch-lightning, shell scripting, software environment management, and high-performance parallel GPU computing. The role involves applying modern AI methods to generative data assimilation, hybrid climate simulation, full model emulation, regional-to-global high-resolution AI autoregressive weather prediction, and dynamical downscaling. Applicants should possess strong skills in geophysical sciences, computer science, or applied math.
Propose, research, prototype, and test innovative research ideas at the intersection of AI and climate science.
Publish groundbreaking research work in top-tier conferences and journals.
Contribute to technology transfer by helping research ideas graduate into actual NVIDIA products.
Utilize high-scale NVIDIA GPUs to conduct cutting-edge research on Earth System Simulation and Analytics.
Develop and scale algorithms for high computational loads using distributed deep learning frameworks like PyTorch.
Drive research projects end-to-end, including software environment management and high-performance parallel GPU computing.
Apply modern AI methods to tasks like generative data assimilation and high-resolution weather prediction.
What we're looking for
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 makes good use of AI.
Proficiency or demonstrable ability to quickly absorb 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 in scaling algorithms for high computational loads (preferred).
Experience developing in a changing software environment and ability to drive research projects end-to-end (preferred).
Expertise in climate domain science, nonlinear physics, or deep familiarity with associated synthetic/observational datasets and physical simulation systems (preferred).
Generative AI
Python
PyTorch
C++
CUDA
Computer Vision
NLP
3D
Parallel Programming
Machine Learning
Deep Learning
Computer Architecture
Multimodal Data
AI for Science
Generative AI
PyTorch
Python
Multimodal Learning
Reinforcement Learning
Computer Vision
Distributed Training
World Models
Robotics
Simulation
Video Understanding
VLMs
Foundation Models
Action-conditioned Simulation
Policy Learning