Job Description
• Develop and implement reduced-degree mechanical performance prediction models by combining FEA with machine learning techniques, leveraging historical datasets from previous glasses products to predict failure modes and structural instability.
• Design and deploy neural network surrogate models (e.g., using PyTorch) integrated directly into FEA solvers (such as Abaqus subroutines) to simulate history-dependent material behaviors and multiscale structural responses efficiently.
• Guide the FEA team for mechanical simulation, structural risk assessment, and design optimization of the display system, specifically applying iterative operator learning to improve out-of-distribution data transferability for new form factors.
• Develop advanced constitutive models for complex materials used in display systems (including metals, polymers, adhesives, and brittle materials) to accurately capture nonlinearities, creep, and fracture mechanics under dynamic loading.
• Perform Bayesian statistical inference and uncertainty quantification to correlate simulation results with noisy experimental metrology data, bridging the gap between theoretical models and physical test results.
• Collaborate with design engineers to connect system PD and module designs with total stack tolerance analysis, ensuring that ML-driven predictions align with physical fit studies and manufacturing capabilities.
• Drive failure analysis activities by simulating damage evolution and crack propagation in quasi-brittle materials, supporting product scalability and reliability teams.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Required Skills & Experience
Requirements:
• Ph.D. or Master’s degree in Mechanical Engineering, Materials Science, Computational Mechanics, or a related field.
• Extensive experience in Finite Element Analysis (FEA) and solid mechanics, with deep expertise in nonlinear dynamics, large deformation, and contact mechanics using tools like Abaqus or ANSYS.
• Proven expertise in developing and applying Machine Learning (ML) models to mechanics problems, including experience with PyTorch, scikit-learn, and building neural network surrogate models for simulation.
• Proficiency in programming languages including Python, C++, Fortran, and MATLAB, specifically for writing user subroutines (e.g., VUMAT/UMAT) and integrating ML inference into FEA workflows.
• Experience with reduced-order modeling, operator learning, or LSTM/RNN architectures for analyzing history-dependent data and spatial-temporal fields.
• Working knowledge of material behaviors including plasticity, creep, and fracture mechanics for ductile and brittle materials.
• Ability to apply analytical and problem-solving skills to analyze complex opto-mechanical systems and identify innovative solutions for reduced-degree performance prediction.
• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams to translate complex simulation results into actionable design guidance.
Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.