Staff Engineer - Advanced Packaging Multiphysics Physics Modeling

Absolics Inc.; Covington (GA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

401K matching

Healthcare coverage

Job summary

Absolics Inc. in Covington, GA seeks a Staff Engineer to own advanced packaging multiphysics physics modeling, from die-level interconnects to buildup layers of system integration.

You will build and validate predictive models for mechanical and electrical performance, enabling design rules for process and product teams and closing the loop with reliability data.

Qualifications

• BS/MS/PhD in a relevant field with strong modeling experience.
• Expertise in multilayer stack modeling and reliability prediction.
• Strong communication and collaboration with cross-functional teams.

Responsibilities

• Lead multiphysics simulations for mechanical and electrical performance.
• Develop and validate predictive models for packaging reliability and SeWaRe-type failures.
• Translate simulation output into design rules for process and product teams.

Skills

FEA modeling

Interlayer stress analysis

Delamination modeling

Cohesive zone modeling

Viscoelasticity

RDL/buildup layer mechanics

Semiconductor packaging processes

Python/MATLAB scripting

Electrical/mechanical co-simulation

Education

PhD or equivalent in mechanical engineering / materials science / semiconductor physics

Tools

ANSYS

Abaqus

COMSOL

Python

MATLAB

Job description

Role Title: Staff Engineer - Advanced Packaging Multiphysics Physics Modeling (Mechanical- Electrical Co-Simulation)

Job Title: Staff Engineer - Advanced Packaging Multiphysics Physics Modeling

Location: Covington, GA

Job Type: Full-Time

Job Description:

This role owns the simulation, modeling and interpretation of Multiphysics behavior across advanced packaging architectures from die level interconnects through buildup layers to system-level integration. The engineer will build and validate predictive models for mechanical (stress, warpage, fatigue, delamination, cracking, SeWaRe) and electrical (signal/power integrity, thermal-electrical coupling) performance, translating simulation output into design rules and go/no-go decisions for process and product teams. Core work spans finite element analysis (FEA) of interlayer/interface stresses, material characterization and constitutive modeling, failure mode prediction (crack initiation, delamination, via cracking, SeWaRe type reliability failures), and RDL/buildup layer mechanical-electrical co-optimization, closing the loop between simulation predictions and physical failure analysis/reliability test data.

Required Skills:

• FEA modeling (ANSYS, Abaqus, or COMSOL) for stress/strain, thermos-mechanical and fracture mechanics analysis in multilayer stacks
• Interface/interlayer stress and delamination modeling (cohesive zone modeling, VCCT, traction-separation laws)
• Material property characterization, and modeling for polymers (dielectrics, mold compounds) metals, (Cu, Ti seed), and glass/ceramic substrates – CTE mismatch, viscoelasticity, plasticity
• Working knowledge of RDL buildup layer, and interposer architectures (organic, glass core) and their process induced stress states
• Failure mode analysis tied to package reliability (thermal cycling, SeWaRe, drop/shock, warpage) with ability to correlate simulation to physical failure analysis (SEM, CSAM, cross-section)
• Electrical performance simulation basics – signal/power integrity or coupled electro-thermal-mechanical modeling
• Strong grasp of semiconductor packaging unit processes (lithography, plating, etch) and how they introduce residual stress
• Scripting/automation for parametric studies (Python, MATLAB, or APDL/Abaqus scripting)
• Ability to translate simulation results into actionable design rules for process/product engineering teams

Preferred Skills

• Experience with panel level packaging reliability prediction
• Exposure to system-level (board + package + die) co-simulation
• DOE/Statistical methods for correlating simulation with experimental reliability data
• Familiarity with glass core interposer or 2.5D/3D heterogenous integration mechanics
• Experience with machine learning assisted surrogate modeling for faster design space exploration

Education:

• PhD or equivalent industry experience in mechanical engineering materials science, or semiconductor device physics
• 401K 6% matching (NO vesting period)
• Healthcare 100% support (Health, Dental, Vision)