Senior Applied Research Scientist – Computational Geometry and Meshingmill

Description

Industrial simulation relies on turning product and device geometry into valid, efficient discretizations. This role advances computational geometry, meshing, simulation-ready representations, and AI-native algorithms for the company's GPU platforms.

You will be an applied researcher building methods that carry design data from CAD to simulation dependably. The work covers geometry, meshing, and discretization algorithms that improve robustness, numerical accuracy, and end-to-end performance across CAE, EDA, semiconductor, and scientific computing workflows.

Responsibilities

• Build algorithms for computational geometry, CAD and CAE interoperability, mesh generation, mesh adaptation, spatial data structures, and curved discretization.
• Research differentiable geometry, AI-native geometry processing, learning-based meshing and discretization, and design-to-simulation workflows for inverse design, simulation-ready digital twins, and autonomous engineering.
• Develop geometry and discretization methods that account for solver and hardware behavior and balance mesh quality, numerical accuracy, robustness, and overall simulation efficiency.
• Define benchmarks covering mesh quality, geometry conversion, discretization accuracy, robustness, solver impact, and end-to-end simulation performance.
• Work with teams across the company's graphics, simulation, and research groups, along with universities and industrial partners in CAE, EDA, chip manufacturing, electronics, and digital twins.

Requirements

• PhD or equivalent experience in computer science, computational geometry, scientific computing, graphics, applied mathematics, computational mechanics, engineering, or a related field.
• 5+ years of experience.
• At least 5 years of proven work in computational engineering, with a background in computational geometry, geometry processing, mesh generation, adaptive discretization, CAD and CAE algorithms, or simulation-ready representations.
• Strong C++ and Python skills, with experience building algorithms for complex geometry.
• Solid grasp of boundary representations, topology, mesh quality, discretization error, numerical robustness, and solver needs, backed by research, software, or industrial results.