layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

Computational Scientist, Structural & Thermal at Periodic Labs | LAYIQ

Periodic Labs is an early-stage startup, and we're looking for someone who can bring technical leadership to modeling structural and thermal behavior in semiconductor devices, not necessarily someone who already has every skill listed below. A strong growth mindset, demonstrated ownership, and a track record of getting up to speed quickly in new technical areas are much more important than experience in semiconductors.
A PhD or equivalent research experience in mechanical engineering, materials science, aerospace engineering, or a closely related field, with a strong foundation in solid mechanics and heat transfer. Early-career candidates with strong research or engineering output are encouraged to apply.
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 is a strong positive signal. Contributions to open-source projects that others actually use are even better.
Strong Python skills, with C++, Julia, or Fortran proficiency a plus. Experience running simulations programmatically at scale rather than through point-and-click tools.
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 that were not obvious from measurement alone.
Genuine curiosity about AI and a desire to work at the boundary of simulation and machine learning.
Strong Candidates May Also Have
Experience with GPU-accelerated FEM, reduced-order mechanical models, surrogate models, or physics-informed neural networks for structural problems.
Familiarity with multiscale mechanics: bridging from atomistic or DFT-informed potentials through molecular dynamics, mesoscale methods, and continuum mechanics.
Deep expertise in thin-film mechanics: residual stress, Stoney equation regimes and their limits, film-substrate interactions, delamination, and stress evolution during deposition.
Experience with wafer-scale mechanics: bow, warp, thermal cycling reliability, packaging-induced stress, or interconnect mechanics in advanced packaging contexts.
Background in fracture mechanics or damage modeling: LEFM, cohesive zone models, phase-field fracture, fatigue, or statistical failure models.
Knowledge of semiconductor metrology, failure analysis, or process integration that gives physical intuition for how models connect to real manufacturing decisions.
Mechanics
Minimum education
: Bachelor's degree or similar experience
Location
: Menlo Park, CA

Computational Scientist, Structural & Thermal

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