Physics Applications - Researcher

What you'll do

• Experiment with classical and learned temporal propagation methods; generate and curate training and verification data.
• Prototype and iterate on new applications with customers, hardening features through deployment.
• Work across physics, AI, software engineering, and computational geometry teams to bring prototypes into customer use.

What they ask for

• Published work leveraging or building a simulation practice.
• At least 2 years using or building physics simulators.
• Applied machine learning experience and working knowledge of modern ML fundamentals and practices.
• Contributed to a production data processing system; able to meet software design standards and maintain CI, regression testing, and validation discipline.

Nice to have

• Applied ML for geometry meshing or accelerating FEM or DFT simulations; experience using simulation for design or data generation.
• Experience moving an early-stage prototype to production at a startup or national lab.

Pay

$190K – $260K USD base salary

Tools

FEM, FEA, Molecular Dynamics, FDTD, Computer Vision, GraphNN, Transformer Architectures, PyTorch

AI focus

Apply machine learning to physics simulation; develop temporal propagation approaches and extend models to transient interactions, deformation, and dynamics.