GPU-Accelerated Multiphysics CFD Solver Engineer

Siemens Digital Industries Software; Meylan; Hybride; EUR 52 800 - 89 700; Plein temps

Résumé du poste

Siemens Digital Industries Software is hiring a CFD Solver Developer to join the M-Star team. You’ll work on GPU-native, multiphysics solver development for complex fluid and particle systems, translating research into production-ready code.

The role covers algorithm development, solver architecture, GPU acceleration, and collaboration with users and support engineers to keep the software scientifically rigorous and practically useful.

Qualifications

• Expertise with Lattice Boltzmann Methods (LBM) for fluid simulation.
• Background in numerical methods for transport physics (fluid dynamics, advection-diffusion, particle mechanics, or heat transfer).
• Writing high-performance physics codes using parallel computing in shared and distributed memory systems.

Responsabilités

• Developing M-Star’s fluid dynamics solver including maintenance, feature addition, algorithm implementation, and validation.
• Translating academic research in numerical methods into a high-performance, easy-to-use software product.
• Modeling a wide range of physics including fluid dynamics, multiphase flows, advection-diffusion, particle mechanics, and heat transfer.
• Implementing meshing algorithms and data structures for GPU architectures in a distributed memory environment.
• Working with support engineers and users to tailor software to current needs.
• Performing validation studies and presenting results at conferences.

Connaissances

Lattice Boltzmann

Numerical methods

High-performance computing

DEM

Multiphase modeling

Mesh generation

GPU CUDA

MPI programming

Multiphysics solver

Outils

CUDA toolkit

Description du poste

Siemens Digital Industries Software is hiring a CFD Solver Developer to join the M-Star team. You’ll work on GPU-native, multiphysics solver development for complex fluid and particle systems, translating research into production-ready code.

The role covers algorithm development, solver architecture, GPU acceleration, and collaboration with users and support engineers to keep the software scientifically rigorous and practically useful.