Material Informatics Intern

and develop compelling ideas and technologies on material formulation and processing. The individual is also expected to contribute to technical presentations, journal articles, white papers as well as IP generation within this role. This position is in Southfield, MI.

Job Responsibilities:

• Applying machine learning and probabilistic design and optimization methods to real-world industrial applications for New Product Introduction (NPI) and New Technology Introduction (NTI).

• Collect and analyze and process materials data for knowledge extraction and actionable insights.

• Accelerate material and process optimization experiment using AI/ML informatic tools.

• Demonstrate technical leadership around material composite processing, material selection and analysis.

• Identify, evaluate, and recommend combined material, design, and manufacturing processes that best meet the application requirements.

• Specify, plan, and oversee analytical and experimental work qualifying the proposed materials and process options.

• Perform hands-on design, analysis, and experimental work as needed to demonstrate technical feasibility.

• Work closely with experimentalists to design experiments to predict and validate the properties and processes for multi-additive material systems.

• Compile and interpret analysis and test results providing conclusions, recommendations, and inputs for other engineers and management to act upon.

Qualifications:

Basic Qualifications:

• Currently enrolled in a Master's or PhD program Graduate student (preferred PhD student) in Mechanical Engineering, Chemical Engineering, Materials Engineering or related field.

• Experience with AI/ML for material and process optimization.

• Proficiency in Python for data processing and machine learning model development.

• Hands-on experience in material development and characterization.

• Ability to read, understand, and modify existing research-grade code with guidance.

• Strong documentation and technical communication skills.

Preferred Qualifications:

• Master of Science degree in materials engineering or related discipline.

• Experience with inverse Machine Learning (ML) algorithms for material and process informatics.

• Demonstrable knowledge in materials and process selection, manufacturing support, and qualification of materials.

• Strong fundamentals in thermal, heat transfer, fluid dynamics, electrical insulation applicable to power electronics, electromagnetics, power conversion, including creating specifications, designing technical solution concepts, and building and testing prototypes to validate models/hypotheses and documenting results.

• Experience in ceramic, metal and polymer materials property measurement, formulation and processing.

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You do not need to disclose your conviction history or participate in a background check until a conditional job offer is made to you. After making a conditional offer and running a background check, if Eaton is concerned about conviction that is directly related to the job, you will be given the chance to explain the circumstances surrounding the conviction, provide mitigating evidence, or challenge the accuracy of the background report.

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