CFD Multiphase & DEM Engineer

🏢 Physicsx · 📍 Singapore · 💼 onsite

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Position Summary & Responsibilities

About us

Re-architecting Engineering for the Age of Intelligence

PhysicsX is the physics AI company for industrials. The company’s mission is to accelerate hardware innovation by overhauling what industrial engineering and manufacturing look like today. PhysicsX is building a new simulation software stack to deliver deep physics AI enablement across the entire engineering lifecycle. The company partners with leading organisations in aerospace & defence, automotive, semiconductors, materials, and energy & renewables, supporting them on some of their most critical and complex challenges. PhysicsX is headquartered in the United Kingdom, with offices in London, New York, and Singapore and an expanding presence in the Bay Area.

Who We’re Looking For

You are a problem solver and builder, passionate about creating practical solutions that help customers make better engineering decisions. You can grasp and apply advanced engineering concepts across multiple industries, and you excel at working directly with internal and external stakeholders, often on-site, to develop high-fidelity simulation models that feed into AI tools that are both useful and used.

You bring deep expertise in fluid mechanics, heat transfer, and multiphase modelling within bioprocess and chemical engineering environments. You are highly proficient in at least one of Star-CCM+, OpenFOAM, or Fluent, and experienced modelling the complex flow behaviour that arises in industrial bioprocess systems. You are adept at automating these tools to create scalable optimisation workflows. Experience in parametric CAD modelling (NX or CATIA) and coding in Python (or the ability to pick up new programming languages quickly) is an advantage.

What you'll do

Proficiency in CFD solvers across open-source OpenFOAM and commercial platforms as a plus (Star-CCM+, Fluent or equivalent), including custom solver and boundary condition development.
Develop multiphase flow models for gas-liquid, solid-liquid, VOF, Euler-Euler/Euler-Lagrange approaches) across a range of industrial and process engineering applications.
Model non-Newtonian and complex fluid rheology modelling, including high-viscosity, shear-thinning, or particle-laden flow regimes
Reactive and coupled-physics flow modelling — link CFD with reaction kinetics, heat transfer, or

🎯 Candidate Preparation Guide For Physicsx Applicants

Key Role Competencies & Evaluation Highlights

Key Role Focus:

Tests world-class applied artificial intelligence capabilities, deep physics simulation expertise, and the ability to solve extreme engineering bottlenecks.

📋 Preparation Priorities (Key Areas to Clarify):

1. Purely academic AI/ML background with no experience applying models to physical, hard-tech domains.
2. Arrogance or dismissal of domain-specific engineering constraints in aerospace, energy, or materials.
3. Inability to write clean, production-grade code under performance constraints.

✨ Recommended Role Alignment Hook:

I build deep-tech AI frameworks that collapse simulation and optimization loops for the world's most complex physical engineering challenges.

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