2027 Summer Intern - Research and Development - Aftertreatment Catalysis

General Motors•Warren, MI

8d•Hybrid

About The Position

General Motors is seeking a motivated student to join its Energy and Propulsion Systems Research team as a Summer Intern in aftertreatment catalysis. The intern will contribute to research supporting next-generation automotive emissions-control technologies, including catalyst performance, durability, materials development, reaction kinetics, system modeling, and data-driven materials discovery. The specific project will be matched to the candidate’s skills and the team’s research priorities, and may involve experimental, computational, modeling, data science, or AI/ML work. The team is re-establishing and advancing GM’s aftertreatment catalysis research capabilities. Research areas include three-way catalysts, platinum-group-metal reduction, catalyst aging and durability, alternative catalyst and substrate materials, hydrocarbon and nitrogen-oxide traps, reaction kinetics, predictive modeling, and AI/ML-enabled materials discovery. The internship is hybrid, with the successful candidate expected to report to Warren, Michigan at least three times per week or at another frequency directed by the business. Start dates are May 24 or June 14, 2027. The intern must be available to work full-time, 40 hours per week during the summer. Applicants must be pursuing a master’s or doctoral degree in a relevant STEM field and meet the stated U.S. Person and work-authorization requirements. GM does not provide immigration-related sponsorship for this role.

Requirements

Currently pursuing a master’s or doctoral degree in chemistry, chemical engineering, materials science, materials engineering, mechanical engineering, computer science, data science, physics, or a related STEM field.
Available to work full-time, 40 hours per week during the summer internship.
Demonstrated interest in at least one of the following: heterogeneous catalysis, reaction engineering, emissions control, materials science, laboratory experimentation and analytical characterization, mathematical modeling, simulation, scientific computing, numerical methods, data science, artificial intelligence, machine learning, or optimization.
Ability to work independently and collaboratively in a multidisciplinary research environment.
Strong analytical, problem-solving, communication, and technical documentation skills.
Must be a U.S. Person (U.S. citizen, U.S. permanent resident, asylee, or refugee) due to export-control restrictions.
Must not require GM immigration sponsorship now or in the future, including sponsorship or other company immigration support.

Responsibilities

Design, conduct, and analyze laboratory experiments for catalyst, washcoat, powder, or aftertreatment core evaluation.
Prepare samples and support testing using laboratory reactor systems and analytical tools.
Investigate catalyst activity, selectivity, conversion efficiency, thermal durability, aging, sintering, and degradation mechanisms.
Apply characterization methods such as Fourier-transform infrared spectroscopy, diffuse-reflectance infrared Fourier-transform spectroscopy, surface-area analysis, chemisorption, microscopy, and spectroscopy.
Develop reaction-kinetic, catalyst-performance, degradation, or system-level models.
Process and interpret experimental data using Python, MATLAB, or similar tools.
Apply statistical learning, machine learning, optimization, or uncertainty quantification to catalyst and materials datasets.
Build data-driven tools to accelerate catalyst screening and reduce reliance on hardware testing.
Explore AI/ML approaches for materials discovery, composition optimization, performance prediction, or experiment planning.
Correlate material properties, operating conditions, and catalyst performance to identify design principles.
Document methods, analyze results, prepare technical summaries, and present findings to research and engineering teams.
Collaborate with researchers, engineers, universities, national laboratories, suppliers, and other GM organizations.
Follow laboratory safety procedures, data-quality practices, and applicable documentation requirements.