Multiphase CFD Engineer for AI-Driven Simulations

PhysicsX Ltd.; Greater London; Hybrid; AUD 120,000 - 170,000; Full time

Job summary

PhysicsX Ltd. is seeking a hands-on CFD specialist to develop high-fidelity multiphase flow models for industrial processes. You will automate CFD workflows, tightly couple simulations with CAD pipelines, and drive DoE studies using NX/CATIA and Python.

You will collaborate with clients and internal teams to translate complex physics into practical AI-enabled engineering solutions, while advancing scalable HPC and GPU-accelerated workflows.

Qualifications

• Experience in fluid mechanics, heat transfer and multiphase modelling within bioprocess and chemical engineering environments.
• Proficient in at least one of Star-CCM+, OpenFOAM or Fluent, and experienced modelling complex industrial bioprocess flows.
• Apt at automating tools to create scalable optimisation workflows; parametric CAD modelling (NX or CATIA) and Python is an advantage.

Responsibilities

• Develop multiphase flow models for gas-liquid, solid-liquid, VOF and Euler-Euler approaches across industrial applications.
• Model non-Newtonian rheology and complex fluid behaviour including high-viscosity and shear-thinning regimes.
• Link CFD with reaction kinetics and heat transfer for reactive and coupled-physics simulations.
• Own meshing strategy for complex geometries, including rotating machinery and internal passages.
• Build CAD-augmented simulation pipelines for automated design optimisation and DoE studies.
• Develop end-to-end multi-physics workflows: geometry cleanup, meshing, solver setup, validation with data.

Skills

Fluid mechanics

Heat transfer

Multiphase modelling

Python

CAD modelling

Tools

OpenFOAM

Star-CCM+

Fluent

NX

CATIA

Job description

PhysicsX Ltd. is seeking a hands-on CFD specialist to develop high-fidelity multiphase flow models for industrial processes. You will automate CFD workflows, tightly couple simulations with CAD pipelines, and drive DoE studies using NX/CATIA and Python.

You will collaborate with clients and internal teams to translate complex physics into practical AI-enabled engineering solutions, while advancing scalable HPC and GPU-accelerated workflows.