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Entry-Level Researcher – Computational Materials Science, Continuum Scales, Materials Discovery
General Motors. Advance computational materials science at continuum length scales for next-generation vehicle and manufacturing applications .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and applying continuum-scale models and simulation workflows in materials science, with a strong foundation in materials thermodynamics, kinetics, and mechanics. Proficient in scientific programming and data analysis, capable of translating computational discoveries into practical solutions while collaborating effectively in multidisciplinary research teams.
Highest-signal resume keywords
Continuum-Scale ModelingFinite-Element AnalysisScientific ProgrammingMaterials ThermodynamicsHigh-Throughput Screening
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Continuum-Scale ModelsNumerical MethodsConstitutive ModelingDamage and FractureMultiphysics SimulationPython ProgrammingC/C++ ProgrammingFortran ProgrammingMATLAB ProgrammingData Analysis
Soft Skills
Strong Communication SkillsMentoring
Tools & Technologies
High-Performance ComputingVersion-Controlled SoftwareReproducible Computational Workflows
Industry Keywords
Materials ScienceComputational ScienceApplied MathematicsMechanical EngineeringICMEScientific Machine LearningUncertainty QuantificationDigital Twins
Tech Stack
Tools & technologiesCloudPythonC++
About the role
Key responsibilities & impact- Advance computational materials science at continuum length scales for next-generation vehicle and manufacturing applications
- Propose research directions, establish technical research plans, and lead collaborative studies
- Develop and apply continuum-scale models, simulation workflows, and data-driven methods
- Connect material composition, microstructure, processing, performance, and engineering requirements
- Guide experimental research and enable efficient materials down-selection
- Translate computational discoveries into practical materials and manufacturing solutions
- Develop physics-based models covering constitutive behavior, phase evolution, transport, damage, fracture, fatigue, thermal response, and multiphysics phenomena
- Build and apply continuum and mesoscale simulation methods
- Integrate thermodynamics, kinetics, mechanics, processing science, and materials data into predictive workflows
- Use simulation, high-throughput computation, optimization, and data-driven methods to screen materials and processing conditions
- Partner with experimental researchers to define experiments, interpret results, quantify uncertainty, and accelerate materials down-selection
- Establish model verification, validation, calibration, uncertainty quantification, and sensitivity-analysis practices
- Drive collaborations with GM engineering teams, universities, national laboratories, software developers, and research partners
- Prepare technical reports, presentations, publications, software documentation, and invention disclosures
- Generate intellectual property
- Assist and mentor other employees
Requirements
What you’ll need- 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 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 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
- Must not require GM immigration sponsorship now or in the future
- Must be a U.S. Person: U.S. citizen, U.S. permanent resident, asylee, or refugee
- Ph.D. strongly preferred
- Preferred experience in ICME, materials discovery, high-throughput screening, optimization, Bayesian methods, active learning, computational thermodynamics, CALPHAD, scientific machine learning, uncertainty quantification, digital twins, parallel/GPU/cloud/cluster computing, scientific software development, experimental validation, publications, intellectual property, and applied engineering or manufacturing solutions
Benefits
Comp & perks- Relocation benefits administration support
- Benefits supporting employee well-being at work and at home
- Reasonable accommodations for applicants with disabilities