Senior CFD Engineer - Multiphase in London

About us PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.

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 customers, 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, including particle-laden flows, fluidised beds, and coupled CFD-DEM. You are highly proficient in at least one of Star-CCM+, OpenFOAM, or Fluent, and experienced with DEM codes such as EDEM, LIGGGHTS, or Rocky. 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. With 3–5 years of industry experience (post-MEng, MSc, or PhD) in a commercial, non-research environment, you are ready to hit the ground running. You are confident setting up simulations independently, interpreting complex results with rigour, and making sound decisions grounded in solid engineering judgement.

What you'll do Independently build complex multi-physics models, from geometry clean-up and meshing through to simulation, post-processing, and integration of experimental data for validation, spanning single-phase, multiphase, and coupled CFD-DEM regimes. Develop and validate DEM models of granular and particle-laden systems, including fluidised beds, pneumatic conveying, mills, aerosols, suspensions and coating processes, applying appropriate contact models, size distributions, and coupling strategies. Build robust parametric CAD models coupled with simulation pipeline automation to execute advanced design optimisation and DoE studies across large parameter spaces. Partner with customers to address complex engineering challenges through advanced simulation and AI solutions. Present results clearly, recommend actionable next steps, and balance accuracy with efficiency under real project deadlines. Work at the intersection of CAE and data science to generate high-quality simulation datasets for training machine learning and deep learning surrogate models. Apply smart sampling strategies to capture the design space efficiently and reduce computational cost. Leverage Flux (our cloud platform) and on-premise HPC resources to accelerate high-fidelity modelling, going beyond standard setup practices to achieve genuine performance gains at scale. Continuously improve engineering best practices, adapting simulation model setups and outputs to support the development of deep learning surrogates and physics-informed ML models. Combine project leadership with a commitment to mentoring junior colleagues, contributing to a culture of collaboration, rigour, and shared growth. Travel globally (North America, Europe, Asia, Oceania) up to 2–3 weeks per quarter to work on-site with customers building solutions together.

What we're looking for Core simulation skills Multiphase CFD: VOF, Euler–Euler, Euler–Lagrange, or mixture models DEM modelling: EDEM, Rocky, LIGGGHTS, or equivalent Coupled CFD–DEM workflows for particle–fluid systems Heat and mass transfer modelling Reacting flows and phase-change processes (advantageous) Proficiency in Star-CCM+, OpenFOAM, or Fluent Engineering and workflow 3–5 years post-graduate experience in industry (not research) MEng, MSc, or PhD in mechanical, chemical, or process engineering Python scripting and simulation automation DoE, surrogate modelling, and design space exploration Parametric CAD modelling (NX or CATIA advantageous) Strong written and verbal communication with technical and non-technical audiences.

Please note, this role is based in London, working 2-3 days per week in our central office.

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.

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.