Senior Applied Research Scientist – Computational Geometry and Meshing

Job Title

Senior Applied Research Scientist – Computational Geometry and Meshing

Role Summary

The role develops computational-geometry, meshing, and discretization methods to translate design data from CAD into simulation-ready representations optimized for GPU platforms.

Work with research and engineering teams to improve robustness, numerical accuracy, and end-to-end simulation performance across CAE, EDA, semiconductor, and scientific-computing workflows.

Experience Level

Senior — requires substantial applied research and engineering experience. The posting requests 5+ years of relevant experience.

Responsibilities

Primary technical responsibilities:

• Design and implement algorithms for computational geometry, mesh generation, mesh adaptation, spatial data structures, and high-order/curved discretization.
• Investigate differentiable geometry, AI-native geometry processing, and learning-based meshing and discretization for design-to-simulation and inverse-design workflows.
• Develop solver- and hardware-aware geometry and discretization methods that balance mesh quality, numerical accuracy, robustness, and runtime performance.
• Define and run benchmarks for mesh quality, geometry conversion, discretization accuracy, robustness, solver impact, and end-to-end simulation throughput.
• Collaborate cross-functionally with teams in Omniverse/OpenUSD, solver engineering, NVIDIA Research, universities, and industrial partners.

Requirements

Must-have technical skills and experience:

• 5+ years of applied experience in computational geometry, geometry processing, mesh generation, adaptive discretization, or related computational engineering work.
• Proven experience developing robust algorithms for simulation-ready representations and discretization with measurable research, software, or industrial impact.
• Proficiency in C++ and Python and experience building production-grade geometry algorithms.
• Understanding of boundary representations, topology, mesh quality metrics, discretization error, numerical robustness, and solver requirements.

Nice-to-have:

• Experience with CAD kernels or formats (Parasolid, ACIS, Open Cascade, STEP/IGES, B-Rep, NURBS, CATIA, NX, Creo, SOLIDWORKS).
• Experience with tetrahedral, hexahedral, polyhedral, anisotropic, adaptive, boundary-layer, curved, or high-order mesh generation.
• Background in isogeometric analysis, remeshing, meshless methods, topology/shape optimization, differentiable geometry, or AI-native mesh generation.
• Experience with geometry repair, feature recognition, parameterization, persistent correspondence, GPU spatial algorithms, or solver-aware adaptation.

Education Requirements

PhD or equivalent practical experience in computer science, computational geometry, scientific computing, graphics, applied mathematics, computational mechanics, engineering, or a related field.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.