Senior Computational Scientist / Software Engineer - Feature Scale Process Simulation will join a team of software developers and computational scientists to develop next-generation physics-based semiconductor process simulation technologies. The role involves designing, implementing, and maintaining computational software that predicts the evolution of nanoscale structures during plasma etch and deposition processes. Key responsibilities include developing numerical algorithms for geometry evolution, particle transport, and surface reaction kinetics while translating physical theories into production-quality code. Candidates will utilize C++, Python, and advanced methods such as Monte Carlo techniques, finite difference or finite element methods, and GPU programming to optimize performance on multicore architectures. The work focuses on the intersection of software engineering and computational physics to solve complex problems in plasma-surface interactions, material transport, and multiphysics modeling for semiconductor manufacturing applications.
Design, implement, and maintain computational software for feature-scale semiconductor process simulation.
Develop physics-based models for plasma-surface interactions, surface chemistry, and material transport.
Translate physical theories and mathematical models into robust, production-quality software code.
Create numerical algorithms for geometry evolution, particle transport, and surface reaction kinetics.
Optimize simulation performance for multicore CPUs and GPU-based computing architectures.
Validate model predictions against experimental data and metrology results.
Investigate machine learning and surrogate modeling to accelerate simulation workflows.
What we're looking for
Ph.D. or M.S. in Physics, Computational Science, Applied Mathematics, Electrical Engineering, Chemical Engineering, Materials Science, Computer Science, or a related technical discipline.
Experience developing numerical simulation or scientific computing software.
Strong software development experience in C++ and Python.
Familiarity developing feature-scale, topography, or process simulation tools for plasma etch and deposition.
Understanding of computational methods including Monte Carlo techniques, numerical optimization, finite difference/element methods, particle transport, geometry evolution, and multiphysics modeling.
Knowledge of plasma physics and plasma-surface interactions (preferred).
Experience with reaction kinetics, surface chemistry, or gas-phase chemistry modeling (preferred).
Experience with high-performance computing, parallel algorithms, GPU programming, distributed computing, computational geometry, level-set methods, ray tracing, or ballistic transport models (preferred).
Reinforcement Learning
Python
C++
Deep Learning
GPU Clusters
Kubernetes
SLURM
High-Performance Computing
Data Pipelines
Simulation
Closed-Loop Simulation
PPO
GRPO
NuRec
Cosmos World Model