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Paid Internship
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21Open Positions

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PhD Research Intern, AI for Climate and Weather Simulation 2026

NVIDIA
Found 1 month ago
Location
Remote, United Kingdom
Duration (Months)
3 Months
Time
Full-time
Work Mode
Remote
Salary
Not disclosed
Visa Help
Not disclosed
Last Verified
1 month ago

Education

  • PhD

Skills & Qualifications

Technical Skills

  • AI
  • generative data assimilation
  • hybrid climate simulation
  • full model emulation
  • AI autoregressive weather prediction
  • dynamical downscaling
  • distributed deep learning training frameworks
  • PyTorch
  • software engineering
  • scaling algorithms
  • climate domain science
  • nonlinear physics
  • physical simulation systems
  • NVIDIA GPUs

Soft Skills

  • creative
  • independent
  • self-starting
  • collaboratively works
  • passion
  • drive
  • curiosity
  • communication skills

Job Description

NVIDIA is looking for research interns with a strong background relevant to applying modern AI methods to re-imagine technology across the Earth System Simulation and Analytics stack. Skills should be relevant to 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 hunting for highly creative, independent and self-starting research interns to help us invent that future. Strong computer scientists with sufficient knowledge of physical domain sciences are welcome. Alternately, very strong domain scientists with sufficient technical skills are, too. Come join a diverse research group that collaboratively works on hard and meaningful interdisciplinary problems with passion, drive and curiosity; that consistently publishes at top venues in climate science and artificial intelligence; and that values real impact on NVIDIA products and the world of academic and government climate prediction at large.

Requirements

  • Currently enrolled in at least the 2nd year of a Ph.D. in the 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, e.g., PyTorch.
  • Strong software engineering skills are necessary.
  • Excellent communication skills.

Related Field

  • AI & Machine Learning

Related Subfield

  • AI Research

Languages

  • English

Nice to Haves

  • 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 -- including the messy parts – are a plus.
  • Expertise in climate domain science, nonlinear physics, or deep familiarity with associated synthetic and/or observational datasets and/or physical simulation systems are a plus.
▶Apply Now

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