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General Motors Research and Development seeks a Researcher to advance computational materials science across continuum scales, guiding experimental work and translating discoveries into materials and manufacturing solutions.
You will develop continuum and mesoscale models, integrate thermodynamics and kinetics, and lead collaborative studies tying composition, processing, and properties to engineering performance.
The Role: As a valued Researcher in the Mechanics, Materials, and Process Research Lab at General Motors Research and Development, you will advance computational materials science at continuum length scales to accelerate the discovery, design, and deployment of materials for next-generation vehicle and manufacturing applications.
You will propose new research directions, establish technical research plans, and lead collaborative studies that connect material composition, microstructure, processing, performance, and engineering requirements.
You will develop and apply continuum-scale models, simulation workflows, and data-driven methods to generate new insights into materials behavior across relevant spatial and temporal scales.
Your work will guide experimental research, enable efficient materials down-selection, and help translate computational discoveries into practical materials and manufacturing solutions.
You will document and communicate results through high-quality technical reports, external publications, presentations, software or workflow documentation, and records of invention.
This position supports the development of advanced materials and manufacturing technologies for future GM products and processes. The researcher will work at the intersection of continuum‑scale simulation, materials discovery, experimental validation, and application‑focused engineering.
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 to work effectively with GM internal and external collaborators.
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.
GM does not provide immigration‑related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1‑B, OPT, STEM OPT, CPT, TN, J‑1, etc).
The position is subject to export control restrictions and requires the successful candidate to be a U.S. Person (U.S. citizen, U.S. permanent resident, asylee or refugee).
Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Warren, MI three times per week, at minimum [or other frequency dictated by the business].
To help facilitate administration of relocation benefits if you are selected, please apply using the permanent address you would move from.
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