Hybrid CFD Solver Developer (LBM) – GPU & MPI

Siemens; Birmingham; Hybrid; GBP 54,000 - 91,000; Full time

Job summary

Siemens Software in the United Kingdom is seeking a CFD Solver Developer to join the M-Star team. You will develop the fluid dynamics solver, implement GPU-accelerated algorithms, and translate research into production-ready code.

Join a hybrid work environment with collaboration across support engineers and users to ensure the software is both scientifically rigorous and practically useful for diverse industries including Life Sciences, Chemical Materials, and Industrial applications.

Qualifications

• Expertise with LBM for fluid simulation.
• Background in numerical methods for transport physics.
• High-performance physics codes in parallel computing.
• Knowledge of DEM for particle mechanics.
• Specialization in multiphase modeling.
• Algorithms for meshing and 3D search.
• Understanding GPU architectures and CUDA.
• MPI programming for multi-GPU development.
• Experience on a large multiphysics solver.

Responsibilities

• Develop 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.

Skills

LBM methods

Numerical methods

Parallel computing

DEM knowledge

Multiphase modeling

CUDA toolkit

MPI programming

GPU architectures

Mesh generation

Fluid dynamics

Tools

CUDA

Job description

Siemens Software in the United Kingdom is seeking a CFD Solver Developer to join the M-Star team. You will develop the fluid dynamics solver, implement GPU-accelerated algorithms, and translate research into production-ready code.

Join a hybrid work environment with collaboration across support engineers and users to ensure the software is both scientifically rigorous and practically useful for diverse industries including Life Sciences, Chemical Materials, and Industrial applications.