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PhysicsX is a physics AI company for industrials, building simulation software and AI tools to accelerate hardware innovation. The company partners with leading organizations in aerospace & defence, automotive, semiconductors, materials, and energy & renewables.
You will independently build complex multi-physics models spanning single-phase, multiphase, and coupled CFD-DEM regimes. Your responsibilities include:
• Develop and validate DEM models of granular and particle-laden systems (fluidised beds, pneumatic conveying, mills, aerosols, suspensions, 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 design-of-experiments (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 (the company's 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.
The company operates with a flat structure where good ideas win regardless of hierarchy. They offer a hybrid model blending time in the New York office with work-from-home flexibility, equity options, 5% 401(k) contribution, private health insurance, enhanced parental leave (3 months full pay paternity, 6 months full pay maternity), 20 days annual leave plus public holidays, personal development support, subsidized Gympass/Wellhub, and flexible spending accounts.
REQUIREMENTS:
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
