Surfaces Engineering - R&D Co-Op

Novelis Global R&T•Kennesaw, GA
•Onsite

About The Position

Novelis is a global leader in aluminum recycling and rolling, providing sustainable aluminum solutions for aerospace, automotive, beverage packaging, and specialty markets. This co-op opportunity is with the Surface team, located in Kennesaw, GA, as part of the 2027 co-op program. The role involves approximately 6 months of work starting May 2027, focusing on establishing the connection between lubricant properties and aluminum forming performance through hands-on experiments. This includes applying lubricants, forming aluminum parts, and characterizing aluminum surfaces.

Requirements

  • Currently enrolled in an accredited bachelor’s, master’s, or Ph.D. program in materials science, chemical engineering, mechanical engineering, or a related technical discipline, with a minimum GPA of 3.5.
  • Must be currently authorized to work in the United States for any employer.
  • Commitment to following all laboratory safety requirements and procedures.
  • Experience with hypothesis-driven experimental design and data analysis.
  • Background in materials characterization, surface science or metal forming.
  • Attention to detail and ability to work independently.
  • Strong teamwork, critical thinking, and problem-solving skills.
  • Good verbal and written communication skills.

Nice To Haves

  • Graduate students are preferred.
  • Experience with aluminum alloys, sheet metal forming, surface characterization, lubricant or coating application methods.
  • One or more years of hands-on laboratory research experience.
  • Familiarity with Origin, Python, MATLAB or other data analysis tools for organizing experimental data, calculating trends, and summarizing results.

Responsibilities

  • Measure key lubricant properties, including lubricity, wetting behavior, and load-bearing performance.
  • Apply thin lubricant coatings to aluminum sheet.
  • Form aluminum parts using forming equipment.
  • Evaluate the surface quality of formed aluminum samples using techniques such as surface topography and scanning electron microscopy (SEM).
  • Correlate lubricant properties with forming performance to guide future lubricant selection.
  • Summarize data and generate reports.
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