Materials Analysis Engineer

Work Location: Durham County, NC

Summary:

Seeking a motivated engineer to join a laboratory and analysis team, focusing on advanced materials characterization, method development, and data analysis using statistical and machine learning techniques.

Responsibilities:

• Operate and maintain a range of advanced materials characterization instruments and ensure their optimal performance.
• Develop, refine, and document laboratory test methods to improve accuracy, reproducibility, and efficiency.
• Prepare metallographic samples, including mounting, polishing, and etching, for analysis.
• Establish and maintain quality control standards and calibration protocols to ensure high-quality data output.
• Perform comprehensive data analysis using statistical and machine learning approaches for materials data interpretation.
• Develop, train, and validate machine learning models to support materials analysis and prediction tasks.
• Integrate and analyze data from various laboratory and industrial data systems to support process improvement.
• Document procedures, results, and method development clearly, and adapt to evolving laboratory and business needs.

Qualifications:

• Bachelor’s degree in Materials Science, Metallurgy, Mechanical Engineering, Chemical Engineering, or a related field.
• Hands-on experience with materials characterization equipment such as SEM, EDS, EBSD, ICP-OES, and metallographic sample preparation.
• Proficiency in data analysis, including statistics, scripting (Python), and data visualization.
• Strong problem-solving skills and ability to innovate in test method development.
• Experience with machine learning frameworks (scikit-learn, PyTorch, etc.).
• Knowledge of materials and mechanical thermodynamics, solidification, or powder metallurgy processes.
• Experience applying simulation tools to materials processing or structural analysis.
• Must be a U.S. Person due to required access to export-controlled information or facilities.
• Experience with Docker and containerized deployment is a plus.
• Familiarity with FastAPI, Flask, or Dash for internal tools and dashboards is preferred.
• Experience integrating industrial data systems (OPC-UA, Modbus, MQTT) is advantageous.
• Exposure to scientific Python tooling (NumPy, pandas) is beneficial.

Published Category: Analytical & Process Development, Technology & Data & AI Solutions