layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

LAYIQ - Entry-Level – Researcher, Aftertreatment Catalysis at General Motors

Conduct research on automotive aftertreatment catalysts, with emphasis on three-way catalyst technologies and their performance, durability, and cost optimization
Design, plan, execute, and document catalyst evaluation studies using laboratory reactor systems and related experimental methods
Develop and assess catalyst structures, formulations, and architectures intended to reduce platinum group metal content while maintaining or improving conversion efficiency and durability
Apply catalyst characterization methods—including FTIR-DRIFTS, porosimetry, BET surface area analysis, chemisorption, transmission electron microscopy, and related techniques—to understand active sites, support interactions, dispersion, and aging
Correlate catalyst composition, structure, surface chemistry, and reactor performance to identify design rules for next-generation aftertreatment materials
Build and maintain high-quality datasets from experiments, literature, simulations, and characterization results, including test conditions, metadata, and data-quality information needed for reproducible modeling
Apply AI/ML methods such as feature engineering, regression, classification, clustering, dimensionality reduction, Bayesian optimization, active learning, and uncertainty quantification to guide catalyst design and experimental planning
Use interpretable and physically informed models to identify catalyst-performance relationships and prioritize designs that are robust across operating conditions, aging histories, and material variability
Close the design-build-test-learn loop by experimentally validating AI/ML-generated catalyst hypotheses and using the results to improve models and select the next experiments
Partner with modeling and simulation teams to develop predictive tools that reduce dependence on hardware-based testing and support catalyst and converter design decisions
Collaborate with universities, national laboratories, suppliers, and internal stakeholders on focused research activities, externally sponsored technical programs, technical reports, research summaries, invention disclosures, presentations, and publications, as appropriate
Required Qualifications: Pursuit/Completion of a PhD degree in one of the following areas: Chemistry, Materials Science, Chemical Engineering, Materials Engineering, or a closely related field
Must be graduating between August 2026 - June 2027
Able to work fulltime, 40 hours per week
Research experience in heterogeneous catalysis, reaction engineering, materials chemistry, surface science, or a closely related area, with interest in automotive aftertreatment applications
Experience designing and conducting laboratory experiments, analyzing data, and drawing scientifically defensible conclusions
Working knowledge of catalyst characterization techniques and the ability to interpret results from methods such as FTIR-DRIFTS, surface area and porosimetry, chemisorption, X-ray methods, electron microscopy, or related tools
Demonstrated ability to connect catalyst composition or structure with reaction performance, selectivity, stability, or degradation mechanisms
Foundational experience with scientific programming and data analysis, preferably using Python, MATLAB, R, or a similar environment
Ability to learn and apply AI/ML methods to scientific problems, including data preprocessing, feature selection, model evaluation, and uncertainty-aware prediction; formal ML specialization is not required
Strong written and verbal communication skills, with the ability to work effectively in multidisciplinary research and engineering teams

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
Experience evaluating catalysts in flow reactors, bench-scale emissions systems, or other controlled reaction environments
Coursework, research, or project experience in machine learning, design of experiments, Bayesian optimization, active learning, digital experimentation, or scientific informatics
Familiarity with kinetic modeling, reaction mechanism development, multiscale modeling, or physics-informed and data-driven modeling approaches
Experience working with high-dimensional, time-series, or multimodal scientific data and communicating model limitations and uncertainty
Publications, patents, conference presentations, or other evidence of research contributions in catalysis, materials, emissions control, AI/ML for science, or related fields
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).
Work Arrangement: 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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Entry-Level – Researcher, Aftertreatment Catalysis

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