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Deep Learning Researcher – PhysicsAI

Siemens Digital Industries Software · Le Caire

Senior 🇬🇧 English
PyTorch TensorFlow Transformers Diffusion models Normalizing flows Graph Neural Networks Finite Element Analysis Computational Fluid Dynamics Partial Differential Equations Numerical methods

وصف الوظيفة

About the role

We are looking for a Deep Learning Researcher to join the PhysicsAI team at Siemens Digital Industries Software. You will work at the intersection of AI and physics‑based simulation, developing novel deep‑learning surrogate models and generative tools that accelerate product design across mechanical, aerospace and civil engineering domains.

Key responsibilities

  • Identify emerging deep‑learning technologies and evaluate their relevance to engineering simulation.
  • Design, implement and test new DL‑based surrogate modelling and generative AI methods on real industrial problems.
  • Integrate successful approaches into the Simcenter PhysicsAI product suite, writing high‑quality production code.
  • Assess gaps in current gen‑AI capabilities and propose future research directions.
  • Collaborate with application engineers to capture customer requirements and translate them into technical solutions.

Required profile

  • Master’s or PhD in Computer Science, Engineering, AI, Mathematics, Physics or a related field.
  • Strong theoretical knowledge of deep‑learning fundamentals and architectures such as transformers, diffusion models, normalizing flows and graph neural networks.
  • Proven expertise in physics‑based simulation methods including finite element analysis, computational fluid dynamics and partial differential equations.
  • Experience with mesh‑based processing algorithms and large, complex code bases.
  • Excellent problem‑solving abilities and clear communication of technical findings.

Required skills

  • PyTorch or TensorFlow
  • Transformers, diffusion models, normalizing flows, Graph Neural Networks
  • Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD)
  • Partial Differential Equations and numerical methods
  • Mesh‑based processing algorithms
  • Large‑scale software development

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Siemens Digital Industries Software

Le Caire