PhD Research Intern, AI-Aided Engineering

Nvidia

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Santa Clara, CA
Employment
Full-time
Posted
3 days ago
Freshness
Confirmed live today

Market check

Salary context

How this pay compares to similar roles

Similar $170k
$101k $239k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $114,400–$225,625.

Based on 240 similar postings.

Employer

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 1463 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1096 roles with salary data.

Most-posted roles

View all roles at Nvidia

At a glance

TL;DR · PhD Research Intern, AI-Aided Engineering

The PhD Research Intern, AI-Aided Engineering – 2027 joins the AI-Aided Engineering team to develop novel AI methods for physical simulation and engineering design. In this role, you will research, design, and implement methods focusing on neural operators, geometric representations, and large-scale learning. You will collaborate with mentors and product groups to transfer research into practical applications. Key responsibilities include training large-scale neural networks, such as vision transformers or large language models, and working with computational fluid dynamics or CAD/NURBS-based geometric modeling. Required skills include Python programming, PyTorch, and a strong research track record in computer science, applied mathematics, physics, or engineering. You will solve technical problems involving geometry encoding, meshes, point clouds, and agentic AI systems for scientific and engineering workflows.

What you'll do

  • Research, design, and implement novel AI methods for physical simulation and engineering design.
  • Develop and evaluate new ideas to advance the field of AI-aided engineering.
  • Train large-scale neural networks, including large language models or vision transformers.
  • Run numerical solvers and analyze simulation results for computational fluid dynamics.
  • Perform CAD/NURBS-based geometric modeling and geometry processing.
  • Collaborate with product groups to transfer research into practical applications.
  • Develop agentic AI systems for tool use or automated scientific workflows.

What we're looking for

  • Pursuing a PhD in Computer Science, Applied Mathematics, Physics, Engineering, or a related field.
  • Strong research track record and the ability to develop and evaluate new ideas.
  • Excellent Python programming skills and experience with PyTorch or a comparable framework.
  • Excellent communication skills and the ability to work independently and collaboratively.
  • Deep expertise in physical simulation and engineering, such as CFD or CAD/NURBS-based geometric modeling.
  • Proven track record training large language models, vision transformers, or other large-scale neural networks.
  • Experience with geometry encoding and learning from meshes, point clouds, or CAD (preferred).
  • Experience developing agentic AI systems for tool use, automated experimentation, or scientific workflows (preferred).

More like this

Similar roles

PhD Research Intern, AI Accelerator Design and VLSI

Nvidia

Santa Clara, CA 11 days ago
VLSI Design AI HW/SW Co-Design Python PyTorch SystemVerilog C++ High-Level Synthesis (HLS) Machine Learning Quantization Tensor Decomposition Digital VLSI Circuits Hardware Accelerator Architecture Tapeout

PhD Research Intern, Fundamental Generative AI

Nvidia

Santa Clara, CA 24 days ago
Generative AI Python PyTorch C++ CUDA Computer Vision NLP 3D Parallel Programming Machine Learning Deep Learning Computer Architecture Multimodal Data AI for Science