Computational Scientist: Structural & Thermal Simulations

Periodiclabs; Menlo Park (CA); On-site; USD 250,000 - 350,000; Full time

Job summary

Periodic Labs is seeking a Computational Scientist to advance structural and thermal simulations for advanced semiconductor devices and materials. The role blends scientific inquiry with software engineering, requiring solid mechanics and heat transfer expertise, and the ability to extend or create solvers when needed.

You will build scalable workflows, validate models against measurements, and contribute to datasets and ML-driven simulation pipelines.

Qualifications

• PhD or equivalent in a related field with strong mechanics/heat transfer foundation.
• Hands-on experience modifying FEM codes or developing solvers.
• Familiarity with open-source frameworks like FEniCS, deal.II or MOOSE.
• Strong Python skills; C++, Julia or Fortran proficiency a plus.
• Deep knowledge of continuum mechanics, constitutive modeling and PDEs.
• Experience linking simulations to experiments and data.
• Curiosity at the AI/ML boundary in simulation.

Responsibilities

• Develop structural and thermal simulation capabilities for semiconductor systems.
• Build or extend solvers when commercial tools are insufficient.
• Model elasticity, plasticity, viscoelasticity, diffusion and thermal effects.
• Validate models with wafer metrology, curvature, DIC and profilometry data.
• Curate datasets with RL researchers to train LLM-driven pipelines.
• Generate datasets for ML training where experiments are costly.
• Design scalable simulation pipelines connecting outputs to data infra and ML.

Skills

Python

C++

Julia

Solid mechanics

Heat transfer

FEM

GPU acceleration

Education

PhD or equivalent in mechanical engineering or materials science

Bachelor's degree or equivalent experience

Tools

FEniCS

deal.II

MOOSE

Python

C++

Julia

Fortran

Job description

Periodic Labs is seeking a Computational Scientist to advance structural and thermal simulations for advanced semiconductor devices and materials. The role blends scientific inquiry with software engineering, requiring solid mechanics and heat transfer expertise, and the ability to extend or create solvers when needed.

You will build scalable workflows, validate models against measurements, and contribute to datasets and ML-driven simulation pipelines.