CFD Simulation Engineer for Large Physics Models – Hybrid London

PhysicsX Ltd.; Greater London; Hybrid; GBP 70,000 - 95,000; Full time

Benefits offered by this job

Equity options

10% employer pension contribution

Private medical insurance

Hybrid work model

Free office lunches

Enhanced parental leave

Bike2Work scheme and Season ticket?

Octopus EV salary sacrifice

Job summary

PhysicsX Ltd. in London is seeking a Simulation Engineer to join the Research team and help build physics-based data generation for large-scale models. You will generate CFD data, develop solvers, and collaborate with ML researchers to fuse physics and learning at scale.

Based in London with a hybrid work model (2-3 days in our central office), you will contribute to pioneering AI-enabled simulation while keeping models accurate and affordable to train. A PhD is preferred but not required.

Qualifications

• Postgraduate degree in engineering or physics; PhD preferred but not required.
• 1–2 years industry CFD experience in aerospace/defence or CPI.
• Experience building numerical/PDE solvers, e.g., in JAX or Warp.
• Hands-on with CFD solvers such as STAR-CCM+ or Ansys Fluent.
• Comfort with a research environment and open-ended problems.

Responsibilities

• Generate simulation data for training large-scale ML models with varied fidelity.
• Develop and implement solvers and numerical methods (e.g., differentiable or GPU-native frameworks).
• Work with multi-fidelity data and CFD tools to produce reference data.
• Collaborate with ML researchers to translate physics into models and improve corpora.

Skills

Industry CFD experience

Numerical solvers

JAX/Warp

Python scripting

Research experience

Education

MSc or PhD in engineering/physics

Tools

Simcenter STAR-CCM+

Ansys Fluent

OpenFOAM

Job description

PhysicsX Ltd. in London is seeking a Simulation Engineer to join the Research team and help build physics-based data generation for large-scale models. You will generate CFD data, develop solvers, and collaborate with ML researchers to fuse physics and learning at scale.

Based in London with a hybrid work model (2-3 days in our central office), you will contribute to pioneering AI-enabled simulation while keeping models accurate and affordable to train. A PhD is preferred but not required.