Process Simulation Engineering Intern

What you'll do

• Build and refine physics-based models of ion and neutral species interactions during plasma etching.
• Calibrate model parameters against measured profiles from SEM and TEM images.
• Design simulation experiments and parameter sweeps to generate training data.
• Build and validate fast machine-learning surrogate models of slower physics simulations.
• Use surrogate models to perform sensitivity analysis and optimize process conditions.
• Write Python tools to automate simulation runs, data processing, and plotting.
• Document the technical workflow and present final results.

What we're looking for

• Currently pursuing an MS or PhD in chemical engineering, physics, materials science, chemistry, or a related field.
• Strong Python skills including hands-on experience building and training models in PyTorch, JAX, or TensorFlow.
• Background in reaction kinetics, transport phenomena, or surface/plasma science.
• Hands-on experience building machine-learning or regression models.
• Strong analytical and communication skills with the ability to work effectively in a team.
• Coursework or research in plasma physics or plasma-surface interactions (preferred).
• Experience with surrogate modeling methods such as Gaussian processes, neural networks, or reduced-order models (preferred).
• Experience with physics-based simulation tools, semiconductor etch processes, or SEM/TEM image analysis (preferred).