Computational Modeling & Simulation Specialist

About The Role

You will develop and validate the multiphysics models that guide our design decisions: coupled thermal, fluid, and structural behavior of our process. You will own verification, validation, and uncertainty quantification for those models, correlate them against experiment, and turn simulation results into engineering decisions with the founding team.

You might be a great fit if you...

• You are rigorous about model validity. You quantify uncertainty rather than trusting an unvalidated result.
• You connect simulation directly to design and experimental decisions.
• You work well under real constraints: tight budgets, hard deadlines, and novel physics at once.
• You communicate model assumptions and limits clearly across disciplines.

• Develop multiphysics models (thermal, fluid, structural, and coupled) of our process.
• Establish verification, validation, and uncertainty quantification (VVUQ) practice for those models.
• Design simulations to test specific hypotheses and discriminate between competing explanations.
• Correlate model predictions against experimental data and drive model improvement.
• Document assumptions, validation status, and confidence for every model that informs a decision.
• Collaborate with process, controls, electrical, and mechanical engineering.
• Contribute to IP development with the founding team.

• Master's or PhD in Mechanical, Aerospace, Physics, Applied Mathematics, or a related field, or a Bachelor's with equivalent experience.
• 2+ years of multiphysics simulation experience (COMSOL, ANSYS, OpenFOAM, or equivalent).
• Strong foundation in finite element or finite volume methods.
• Thermal-fluid or structural modeling experience.
• Scripting for simulation and data analysis (Python, MATLAB, or equivalent).
• Experience validating models against experimental data.

• Formal VVUQ methods and uncertainty quantification.
• Coupled multiphysics or moving-mesh modeling.
• High-performance computing.
• Machine learning for physics, especially physics-informed neural networks (PINNs) or other physics surrogate modeling.
• Acoustic physics modeling.
• Reduced-order modeling.

• Y Combinator and NSF-backed startup.
• Stock options or equity.
• Direct collaboration with the founding team on a process with no direct commercial equivalent.
• A lean, on-site environment where your technical judgment shapes product direction.
• The opportunity to file patents and contribute to a growing IP portfolio.
• Flexible working arrangements and a culture that respects your time and autonomy.