Software Intern

BETA CAE Systems International AG

Austin, United States
Graph neural networks (gnns)
Ai-driven approaches
Engineering and physics-based applications
Explore and apply AI/ML techniques, including Graph Neural Networks (GNNs), to graph- or mesh-structured engineering data

Job Summary

  • Explore and apply AI/ML techniques, including Graph Neural Networks (GNNs), to graph- or mesh-structured engineering data.
  • Assist in developing AI-driven approaches for engineering and physics-based applications, such as thermal and structural simulation.
  • Work with researchers and engineers to prototype, test, and evaluate AI models in simulation workflows.

Matching Summary

Explore and apply AI/ML techniques, including Graph Neural Networks (GNNs), to graph- or mesh-structured engineering data.

Skills & Requirements

Must-have

  • Graph Neural Networks (GNNs)
  • AI-driven approaches
  • engineering and physics-based applications
  • simulation workflows
  • C/C++ and Python programming
  • data structures and algorithms

Nice-to-have

  • mesh-based data structures
  • graph representations
  • EDA, CAD/CAE, simulation domains
  • performance optimization
  • parallel computing
  • GPU acceleration

Key Requirements

  • Bachelor’s or higher in Computer Science, Engineering, or related field
  • Familiarity with basic software development practices
  • Strong collaboration skills, curiosity, and motivation to learn

Work Rights

Not specified

Tailored Resume

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