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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.
Large Physics Models need data, and the quality, diversity and cost of that data shape is what we need to define. As a Simulation Engineer in our Research team, you will build the simulation side of that foundation. You’ll work in a research environment, alongside ML researchers and engineers, on how physics-based simulation and machine learning can be combined in ways that haven’t been done before.
You’ll be working at the frontier of Large Physics Model development, shaping new AI paradigms for our customers to benefit from in the future. You will aid in data generation, how, and at what fidelity, so that the models we build are both accurate and affordable to train.
What you will do- Generate simulation data for training large-scale ML models, drawing on a mix of methods and fidelity levels.
- Develop and implement solvers and numerical methods, potentially in modern differentiable or GPU-native frameworks such as JAX or NVIDIA Warp.
- Work with multi-fidelity data: understand tradeoff between fidelity and CFD simulators and how the two can be combined.
- Use commercial and open-source CFD tools to produce reference data
- Collaborate closely with ML researchers and engineers, translating between the physics and the models, and helping the team get the best corpus possible.
- Contribute to the technical direction of our data generation work and flag the simulation investments that will unlock research progress.
- A postgraduate degree (MSc or PhD) in engineering, applied mathematics, physics or a related field, ideally with research involving numerical analysis of PDEs or computational engineering. A PhD is preferred but not required.
- At least 1-2 years of industry experience in CFD, ideally in turbomachinery, aerospace, defence or the chemical and process industries (CPI).
- Experience developing numerical solvers or PDE solvers, for example in JAX, Warp or a comparable framework.
- Hands-on experience with at least one commercial CFD solver, such as Simcenter STAR-CCM+ or Ansys Fluent.
- Comfort working in a research setting, where problems are open-ended and the path isn’t always clear.
- Practical experience with OpenFOAM.
- Exposure to ML or surrogate model development, or experience working directly with ML teams.
- Work at the frontier of Large Physics Models, in a team where simulation expertise shapes the research direction.
- Join a research environment with real access to ML talent and compute.
- Influence how we think about data, fidelity and physics in AI.
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 Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.
And it doesn’t stop there …
🚀 Equity options - share meaningfully in the company you’re helping to build.
🏦 10% employer pension contribution - because investing in future matters.
🍽️ Free office lunches - to keep you energised and focused.
👶 Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.
🍼 YellowNest nursery scheme - to help working parents manage childcare costs.
☀️ 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.
🏥 Private medical insurance - 100% employee cover, giving you complete peace of mind.
💪 Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing.
👀 Eye tests - because good work depends on good health.
📈 Personal development - dedicated support for learning, development, and leveling up over time.
💛 Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it.
🚲 Bike2Work scheme and 🚆 Season ticket loan - to make getting to work easier and greener.
🚗 Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric.
🔎 Watch this space, we’re continuing to build this as we grow…
PhysicsX London, England Office
Victoria House 1 Leonard Circus, London, United Kingdom, EC2A 4DQ
