Computational Mechanics Scientist (Structural Solver)

About the role

Flexcompute is a cutting-edge technology startup specializing in ultra-fast simulation technology. Our products are utilized by companies in designing and optimizing technology products, with applications ranging from designing airplanes and cars to wind turbines and quantum computing chips. Our customer base includes both household names and startups in emerging industries. Our company was founded by world-renowned leaders in simulation technology from Stanford University and MIT. Backed by top VC firms, we are poised to disrupt the billion-dollar engineering simulation industry with our fast-growing trajectory.

Requirements

• Education: Ph.D. in Applied Mechanics, Physics, Applied Mathematics, or a related field.
• Deep Physics Intuition: You possess an intuitive grasp of continuum mechanics—elasticity, plasticity, contact mechanics, and wave propagation. You can predict how a structure should behave before the simulation runs.
• Advanced Numerical Analysis: You have a theoretical mastery of numerical PDEs. You can mathematically prove the consistency, stability, and convergence of a scheme. You understand the trade-offs between implicit/explicit integration and various spatial discretizations.
• Strong General Programming: Proficiency in at least one high-level language (C++, Python, Julia, Rust, or Fortran) with a focus on algorithmic efficiency. You understand data structures, computational complexity (Big O), and how to write maintainable research code.
• First-Principles Thinking: Demonstrated ability to solve novel problems where no textbook solution exists.
• (Preferred but not required): Interest in learning High-Performance Computing (HPC) and GPU architecture.
• Experience with C++ for scientific computing.
• Exposure to multi-physics coupling (fluid-structure interaction, thermal-stress).

Key Responsibilities

• Solver Formulation: Derive and implement governing equations for structural mechanics, ensuring thermodynamic consistency and physical accuracy across linear and non-linear regimes.
• Numerical Architecture: Design the core numerical framework. Determine the optimal discretization strategies (FEM, DG, IGA, etc.) to balance stability, accuracy, and computational cost.
• Algorithmic Development: Write clean, modular, and efficient algorithms to solve large-scale systems of equations.
• Physics-Driven Validation: Diagnose solver behavior not just as code execution, but as physical modeling. Distinguish between numerical instability and physical phenomena.

Benefits

• Collaborative Autonomy: We operate with high trust. You own your module, but you have immediate access to world-class experts in electromagnetics and fluid dynamics for cross-domain problems.
• Continuous Learning: We host regular internal seminars where team members teach each other—from "Advanced Linear Algebra" to "GPU Memory Hierarchies."
• Compensation: Competitive salary + meaningful equity in a fast-growing startup.
• Well-being: Comprehensive Medical, Dental, and Vision insurance; 401(k); and a gym/fitness allowance.
• Environment: A flat hierarchy where the "best idea wins," regardless of job title.