Entry-Level Researcher – Aftertreatment Catalysis

General Motors

. Conduct research on automotive aftertreatment catalysts, especially three-way catalyst technologies .

Posted 10/12/2026full-timeWarren • Michigan • United StatesEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in heterogeneous catalysis and catalyst characterization, with a strong foundation in AI/ML methods for scientific problem-solving. Capable of designing and executing laboratory experiments while effectively collaborating with multidisciplinary teams.

Highest-signal resume keywords

PhD In Chemistry, Materials Science, Chemical Engineering, Or Related FieldResearch Experience In Heterogeneous CatalysisCatalyst Characterization TechniquesAI/ML Methods ApplicationScientific Programming In Python, MATLAB, Or R

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Catalyst Evaluation StudiesCatalyst Structure DevelopmentData AnalysisExperimental DesignCatalyst Performance CorrelationFeature EngineeringRegressionClassificationDimensionality ReductionBayesian Optimization

Soft Skills

Strong Written CommunicationStrong Verbal CommunicationTeam Collaboration

Tools & Technologies

Laboratory Reactor SystemsFTIR-DRIFTSX-Ray MethodsElectron MicroscopyFlow Reactors

Industry Keywords

Automotive Aftertreatment CatalystsThree-Way Catalyst TechnologiesAutomotive Emissions ControlCatalyst AgingPrecious-Metal Utilization

Tech Stack

Tools & technologies

ElectronPythonRay

About the role

Key responsibilities & impact

Conduct research on automotive aftertreatment catalysts, especially three-way catalyst technologies
Design, plan, execute, and document catalyst evaluation studies using laboratory reactor systems
Develop and assess catalyst structures, formulations, and architectures to reduce platinum group metal content while maintaining conversion efficiency and durability
Apply catalyst characterization methods to understand active sites, support interactions, dispersion, and aging
Correlate catalyst composition, structure, surface chemistry, and reactor performance to identify design rules
Build and maintain high-quality datasets from experiments, literature, simulations, and characterization results
Apply AI/ML methods including feature engineering, regression, classification, clustering, dimensionality reduction, Bayesian optimization, active learning, and uncertainty quantification
Use interpretable and physically informed models to identify catalyst-performance relationships
Experimentally validate AI/ML-generated catalyst hypotheses and improve models through the design-build-test-learn loop
Partner with modeling and simulation teams to develop predictive tools for catalyst and converter design
Collaborate with universities, national laboratories, suppliers, and internal stakeholders on research activities, technical reports, presentations, invention disclosures, and publications

Requirements

What you’ll need

Pursuit or completion of a PhD in Chemistry, Materials Science, Chemical Engineering, Materials Engineering, or a closely related field
Must be graduating between August 2026 and June 2027
Able to work full-time, 40 hours per week
Research experience in heterogeneous catalysis, reaction engineering, materials chemistry, surface science, or a closely related area
Experience designing and conducting laboratory experiments, analyzing data, and drawing scientifically defensible conclusions
Working knowledge of catalyst characterization techniques, including FTIR-DRIFTS, surface area and porosimetry, chemisorption, X-ray methods, and electron microscopy
Ability to connect catalyst composition or structure with reaction performance, selectivity, stability, or degradation mechanisms
Foundational experience with scientific programming and data analysis, preferably Python, MATLAB, R, or similar
Ability to learn and apply AI/ML methods to scientific problems
Strong written and verbal communication skills and ability to work in multidisciplinary teams
Must be a U.S. Person: U.S. citizen, U.S. permanent resident, asylee, or refugee
Must not require GM immigration sponsorship now or in the future
Subject to export control restrictions
Preferred: research experience in three-way catalysts, automotive emissions control, oxygen storage materials, catalyst aging, sulfur or thermal durability, precious-metal utilization, or catalyst-support interactions
Preferred: experience evaluating catalysts in flow reactors, bench-scale emissions systems, or controlled reaction environments
Preferred: coursework, research, or project experience in machine learning, design of experiments, Bayesian optimization, active learning, digital experimentation, or scientific informatics
Preferred: familiarity with kinetic modeling, reaction mechanism development, multiscale modeling, or physics-informed and data-driven modeling
Preferred: experience with high-dimensional, time-series, or multimodal scientific data
Preferred: publications, patents, conference presentations, or other research contributions

Benefits

Comp & perks

Relocation benefits administration support
Employee well-being resources through GM Total Rewards
Reasonable accommodations for applicants with disabilities
Inclusive workplace and equal employment opportunities