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Computational Scientist, Structural & Thermal

Periodic Labs· Science
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Menlo Park, CA$250k - $350kFull-timePosted 10mo ago

About the role

Computational Scientist to develop structural, thermal, and coupled thermo-mechanical simulation capabilities for semiconductor systems and advanced materials. Combines scientific understanding with software engineering to build, extend, and automate solvers and simulation pipelines.

Responsibilities

  • Develop agent-based structural and thermal simulation capabilities for semiconductor systems, including wafer stress and warpage, thin-film residual stress, thermo-mechanical reliability, thermal budget modeling, process-induced deformation, fracture and delamination, and coupled heat-stress problems.
  • Build or extend custom solvers where commercial FEA tools are too slow, opaque, or inflexible, including custom FEM implementations, phase-field fracture models, crystal plasticity codes, thin-film mechanics frameworks, or reduced-order mechanical models, written in Python, C++, or Julia.
  • Model materials behavior at the required physics level: elasticity, plasticity, viscoelasticity, creep, fracture, diffusion-induced stress, thermal expansion mismatch, interfacial mechanics, and materials evolution under process conditions.
  • Validate models against experimental measurements including wafer metrology, curvature and bow measurements, DIC, profilometry, nanoindentation, or failure analysis data.
  • Design and curate evaluation datasets in collaboration with RL researchers to train LLMs capable of directing complex simulation pipelines.
  • Generate simulated datasets for ML training in regimes where experimental coverage is expensive or difficult to achieve.
  • Build and automate simulation pipelines at scale, architecting workflows that connect simulation outputs to data infrastructure, ML systems, and autonomous experimentation loops.

Qualifications

  • PhD or equivalent research experience in mechanical engineering, materials science, aerospace engineering, or a closely related field, with strong foundation in solid mechanics and heat transfer.
  • Hands-on experience with computational mechanics at the code level: writing or substantially modifying FEM codes, implementing constitutive models, or developing custom solvers for structural or thermal problems.
  • Familiarity with open-source simulation frameworks such as FEniCS, deal.II, MOOSE, or similar.
  • Strong Python skills, with C++, Julia, or Fortran proficiency a plus.
  • Deep understanding of solid mechanics theory: continuum mechanics, tensor formulations, constitutive modeling, variational methods, and numerical methods for PDEs.
  • Experience using mechanics or thermal simulations to explain experimental observations, guide materials or process decisions, or surface failure mechanisms.
  • Genuine curiosity about AI and a desire to work at the boundary of simulation and machine learning.

Skills

Required:Solid mechanicsFEM and constitutive modelingProgramming languagesSimulation validation
Nice to have:Open-source frameworksAI/ML synergy

Benefits

  • Equity
Last updated Sep 30, 2026. Interested? Apply on the company site.

About Periodic Labs

From bits to atoms.

Periodic Labs is an artificial intelligence research company pioneering the next leap in scientific discovery. We operate at the intersection of machine learning and scientific experimentation under the thesis that that true understanding of the universe is only possible by interacting and experimenting on it.

artificial intelligencescientific discoverymachine learningscientific experimentation
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