---
title: 'CFD Engineer - Multiphase at PhysicsX'
canonical: 'https://feeny.ai/job/cfd-engineer-multiphase-physicsx-perth-h3xvsadgm91j'
type: 'job'
last_seen: '2026-10-15'
---

# CFD Engineer - Multiphase at PhysicsX

- **Company:** PhysicsX
- **Location:** Perth, Australia
- **Posted:** 2026-10-05
- **Last confirmed live:** 2026-10-15
- **Apply:** https://job-boards.eu.greenhouse.io/physicsx/jobs/4997084101

## Job description

## 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

- 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 domain-specific process models (e.g. biokinetic, combustion or electrochemical frameworks)
- Own meshing generation and strategy for complex industrial geometries, including rotating machinery, internal flow passages, spargers and free-surface interfaces
- Build robust parametric CAD models (NX, CATIA or equivalent) tightly coupled with simulation pipelines, enabling automated design optimisation and DoE studies
- Multi-physics model development end-to-end: geometry clean-up, meshing, solver setup, post-processing and experimental data integration for model validation
- Scale-up/scale-down methodology: translate small-scale experimental data to full-scale CFD models and iterating model fidelity against physical measurements
- HPC: job scheduling, MPI-based distributed computing, GPU acceleration and performance tuning for large-mesh transient simulations on cloud (Flux) and on-premise resources
- Surrogate modelling and ML-CFD coupling: build reduced-order or AI surrogate models from high-fidelity CFD data to support design space exploration and process optimisation
- Data pipeline literacy: structure and curate CFD output datasets for downstream AI/ML training, active learning and Pareto optimisation workflows; applying data sampling techniques (LHS, quasi-random, adaptive) to efficiently cover design space
- Experimental validation workflows: compare simulation predictions against physical test data, interpreting discrepancies and systematically improving model fidelity
- Customer-facing delivery: partner with clients to scope and address complex engineering challenges via CAE and AI solutions; communicating results clearly, recommending actionable next steps and balancing accuracy with efficiency under commercial deadlines
- Proficiency in CFD solvers across open-source OpenFOAM and commercial platforms comes as a plus (Star-CCM+, Fluent or equivalent), including custom solver and boundary condition development.

Our delivery teams drive innovation to turn AI models into practical solutions - read our blog to learn more about how you’ll contribute to this exciting journey!

https://www.physicsx.ai/newsroom/how-delivery-makes-physical-ai-work-in-the-real-world

## What we offer

Build what actually matters

Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.

Learn alongside exceptional people

Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.

Influence over hierarchy

We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.

Sustainable pace, long-term ambition

Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our New York office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.

We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.

We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.

## About PhysicsX

## Company Overview
- **One-liner**: PhysicsX builds an AI-native software stack for physics simulation and engineering design, enabling advanced industries to accelerate innovation by orders of magnitude.
- **Entity Type**: Private (Series C)
- **Headquarters**: London, United Kingdom
- **Founded**: 2019
- **Founders**: Jacomo Corbo (CEO & Co-Founder) and a Co-Founder & Chairman

## Core Business
- **Primary industries**: Aerospace & Defense, Automotive, Semiconductors, Materials, Energy & Renewables
- **Target customers**: Large industrial organizations (B2B Enterprise) – engineers and teams designing and operating complex physical systems
- **Mission**: Empower industrial organizations to build beyond human imagination and address the defining challenges of our time, with a focus on climate and human health impact

## Products & Services
- **PhysicsX Platform** (SaaS + embedded engineering): An AI-native software stack that unifies simulation, physics AI, data, and engineering applications. Integrates with existing toolchains (CAD, CAE, PLM) and accelerates simulation by orders of magnitude, enabling engineers to explore larger design spaces and move from concept to validated design in days.

## Market Standing
- **Valuation**: Approximately $2.4B (as of Series C in August 2026)
- **Key Metric**: Total funding ~$487M (including $300M Series C, $135M Series B, $32M Series A, $20M from NVentures). Revenue is generating but not publicly disclosed (LinkedIn estimates ~$1M, but company is early-stage revenue generating).
- **Notable Investors/Partners**: Atomico (led Series B), General Catalyst (led Series A), NVentures (NVIDIA’s venture arm), NVIDIA (strategic partner), Siemens (collaboration on data center power infrastructure)
- **Growth Signals**: 
  - Series C oversubscribed $300M at $2.4B valuation (Aug 2026)
  - Headcount growth of 71% YoY (LinkedIn: 226 employees; PitchBook: 350 employees post-C)
  - Forward-deployed engineers embedded in customer programs
  - Open standards for physics AI powered by NVIDIA (March 2026)

## Competitive Advantages
- **True AI-native platform**: Physics AI is built as a core primitive, not bolted onto legacy tooling. Uses advanced models like Fourier Neural Operators to simulate physics at speeds unattainable with traditional CFD/FEA.
- **Embedded deployment model**: Forward-deployed engineers work alongside customers on live problems, ensuring measurable outcomes and deep domain integration.
- **Focus on hardest problems**: Targets extreme complexity (aerospace, semiconductors, climate tech) where speed of development is critical and margins for error are zero.
- **Strategic partnerships**: Deep collaboration with NVIDIA (compute, open standards) and Siemens (infrastructure AI).

## Strategic Focus
- Continue scaling the platform across multiple industrial verticals, with emphasis on the climate transition (energy, materials efficiency) and human health (medical devices, supply chain).
- Expand the "Large Physics Models" research program and open standards initiatives.
- Grow the global team (currently 350+ across UK and US) with strong emphasis on research, product engineering, and forward deployment.

## Why Work Here
- **Culture**: Grounded visionaries, moving fast with trust and ambition. Values include "we make stuff happen" and "we form a community in which people can grow."
- **Work environment**: Hybrid (2-3 days in office per week); offices in London (Shoreditch) and New York (Downtown Manhattan). Visa sponsorship and relocation support available.
- **Benefits**: Generous pension contributions, health insurance, enhanced parental support, development opportunities.
- **Engineering culture**: Work on the hardest problems in industry – physics, AI, and engineering collide. Small, high-autonomy teams. Interview process includes pairing and in-person final rounds.
- **Diversity**: Committed to equal opportunities; strongly encourages underrepresented groups to apply.

## Sources
1. [PhysicsX.ai](https://www.physicsx.ai/) – company website
2. [PhysicsX About](https://www.physicsx.ai/about) – mission, team, challenge
3. [PhysicsX Careers](https://www.physicsx.ai/careers) – culture, benefits, interview process
4. [LinkedIn](https://uk.linkedin.com/company/physicsx) – employee count, funding, headcount growth
5. [PitchBook](https://pitchbook.com/profiles/company/529644-70) – valuation, Series C, founding year

## Other roles at PhysicsX

- [Delivery Engineer](https://feeny.ai/job/delivery-engineer-physicsx-singapore-5wsdrs5mzky7) — Singapore
- [Simulation Engineer: FEA & Multi body simulation](https://feeny.ai/job/simulation-engineer-fea-multi-body-simulation-physicsx-new-york-4w9jhnwnw2zm) — New York, NY
- [Staff Software Engineer, Infrastructure - Python & Kubernetes](https://feeny.ai/job/staff-software-engineer-infrastructure-python-kubernetes-physicsx-london-h1qnwfgah3gg) — London, United Kingdom
- [Events & Experiences Manager](https://feeny.ai/job/events-experiences-manager-physicsx-london-hr3ewjq0yfww) — London, United Kingdom
- [Enterprise IT Engineer](https://feeny.ai/job/enterprise-it-engineer-physicsx-new-york-zm2b5bn4hxpq) — New York, NY
- [Lead IT Engineer](https://feeny.ai/job/lead-it-engineer-physicsx-london-q1fk60zjd3m8) — London, United Kingdom
- [Join Our Talent Community](https://feeny.ai/job/join-our-talent-community-physicsx-london-ff82t2dkq2w4) — London, United Kingdom
- [CFD Engineer](https://feeny.ai/job/cfd-engineer-physicsx-new-york-ed2z3r3afh4y) — New York, NY
- [Resourcing Manager (Delivery)](https://feeny.ai/job/resourcing-manager-delivery-physicsx-london-6nb5k6xmx8fw) — London, United Kingdom
- [Senior Simulation Engineer - Electromagnetics Specialist](https://feeny.ai/job/senior-simulation-engineer-electromagnetics-specialist-physicsx-new-york-q1a4azp2whvc) — New York, NY