Researcher

About the Role

As a Researcher in the Mechanics, Materials, and Process Research Lab, you will advance computational materials science at continuum length scales to accelerate materials discovery, design, and deployment for next-generation vehicle and manufacturing applications. You will:

• Propose new research directions.
• Establish technical research plans.
• Lead collaborative studies connecting material composition, microstructure, processing, performance, and engineering requirements.
• Develop and apply continuum-scale models, simulation workflows, and data-driven methods to generate insights into materials behavior.
• Guide experimental research, enable efficient materials down-selection, and translate computational discoveries into practical solutions.
• Document and communicate results through technical reports, external publications, presentations, software/workflow documentation, and records of invention.

Key Responsibilities

• Plan and execute collaborative research in computational materials science, with emphasis on continuum-scale materials behavior and materials discovery.
• Develop physics-based models for composition–process–structure–property relationships, including constitutive behavior, phase evolution, transport, damage, fracture, fatigue, thermal response, and multiphysics phenomena.
• Build and apply continuum and mesoscale simulation methods such as finite-element, phase-field, crystal-plasticity, computational fluid dynamics, reaction–diffusion, or cellular automata.
• Integrate thermodynamics, kinetics, mechanics, processing science, and materials data into predictive computational workflows.
• Use simulation, high-throughput computation, optimization, and data-driven methods to screen candidate materials, compositions, processing conditions, and architectures.
• Partner with experimental researchers to define informative experiments, interpret results, quantify uncertainty, and accelerate materials down-selection.
• Establish model verification, validation, calibration, uncertainty quantification, and sensitivity-analysis practices.
• Connect computational materials insights to manufacturing processes and vehicle-relevant performance requirements.
• Drive internal and external collaborations with GM engineering teams, universities, national laboratories, software developers, and research partners.
• Maintain awareness of the state of the art in continuum mechanics, computational materials science, materials informatics, scientific machine learning, and related disciplines.
• Prepare timely, high-quality technical reports, presentations, publications, software documentation, and invention disclosures.
• Generate intellectual property.
• Assist and mentor other employees.

Qualifications

Required Qualifications

• Advanced degree (M.S. or Ph.D.) in Materials Science and Engineering, Mechanical Engineering, Computational Science, Applied Mathematics, Physics, Chemistry, or a closely related field.
• Must be graduating between August 2026 - June 2027.
• Able to work fulltime, 40 hours per week.
• Strong foundation in materials thermodynamics, kinetics, mechanics, transport, numerical methods, and structure–property relationships.
• Experience developing or applying continuum-scale models to materials, manufacturing processes, or engineering systems.
• Experience with one or more of the following: finite-element analysis, phase-field modeling, crystal plasticity, constitutive modeling, damage and fracture, multiphysics simulation, reaction–diffusion, or process simulation.
• Experience connecting material chemistry, microstructure, processing history, and performance through computational models.
• Proficiency in scientific programming and data analysis using tools such as Python, C/C++, Fortran, MATLAB, Julia, or similar languages.
• Experience with numerical algorithms, high-performance computing, version-controlled software, and reproducible computational workflows.
• Ability to formulate research questions, translate physical assumptions into models, and communicate model limitations clearly.
• Experience working in multidisciplinary research teams.
• Strong written and verbal communication skills.

Preferred Qualifications

• Ph.D. strongly preferred.
• Experience with one or more of the following:
• Integrated Computational Materials Engineering (ICME) and materials process–structure–property modeling.
• Materials discovery, high-throughput screening, combinatorial design, optimization, Bayesian methods, or active learning.
• Phase-field, crystal-plasticity, mesoscale, finite-element, multiphysics, or reduced-order modeling.
• Computational thermodynamics, CALPHAD, kinetics, phase transformation, precipitation, solidification, or microstructure evolution.
• Scientific machine learning, surrogate modeling, uncertainty quantification, sensitivity analysis, or inverse problems.
• Digital twins, process–structure–performance linkages, or integration of simulation with manufacturing data.
• Parallel computing, GPU acceleration, cloud or cluster computing, and scalable simulation workflows.
• Scientific software development, open-source contributions, workflow automation, or user-defined solver development.
• Experience coupling continuum-scale predictions with experimental validation and characterization data.
• Demonstrated publication record and/or intellectual property generation.
• Experience transitioning computational materials insights into applied engineering or manufacturing solutions.
• Experience communicating technical results to both specialist research audiences and product-development or manufacturing teams.

Work Arrangement: Hybrid (report to Warren, MI three times per week, at minimum).

This position requires the successful candidate to be a U.S. Person.