Overview:

Oak Ridge National Laboratory (ORNL) is seeking a Research Professional to support research and development in Smart Scalable Manufacturing with an emphasis on Artificial Intelligence (AI) and emerging technologies. You will work on integrating AI, automation, and smart manufacturing principles, enhancing process efficiency, and materials supply chain. This position resides in the Composite Science and Technology Section in the Manufacturing Science Division (MSD) of the Energy Science and Technology Directorate at ORNL.

You will play a key role in advancing AI-enhanced manufacturing, including digital twins, process automation, and data-driven materials supply chain optimization. The role includes working with industry partners and leveraging ORNL’s Manufacturing Demonstration Facility (MDF) to develop scalable, AI-powered solutions for supply chain integration and biobased materials integration, and process optimization.

More About UT-ORII:

The University of Tennessee-Oak Ridge Innovation Institute is a partnership of Oak Ridge National Laboratory (ORNL) and UT created to prepare interdisciplinary leaders in energy, science, and technology and develop a world-class workforce for industry, government, and academia that will drive innovation and create the industries of the future. More information is available at University of Tennessee - Oak Ridge Innovation Institute (utorii.com). Today’s energy economy is driven by disruptive technologies and swift change. The US is in a global competition for jobs, talent, and investment. To successfully compete, we must develop leadership talent in research and development (R&D), encourage entrepreneurship, and create an educational environment that promotes rapid innovation and attracts skilled professionals. Leveraging a 75-plus-year UT-ORNL partnership, UT and ORNL have developed joint institutes, joint facilities, interdisciplinary PhD programs, and comprehensive joint faculty arrangements, including 17 Governor’s Chairs recruited for the significance of their impacts in their fields. UT-ORII’s overall goal is to become a center for convergent research and talent development, helping maintain US prominence as a global innovation leader and providing tangible benefits to Tennessee.

Major Duties/Responsibilities: 

• Develop AI-enhanced sustainable manufacturing solutions by integrating machine learning, visual inspection such as cameras, sensors, feedback control, and predictive analytics into industrial processes.
• Develop and apply smart manufacturing techniques, including automation, robotics, and industrial IoT (IIoT) to improve material efficiency and reduce waste.
• Design and conduct experiments to validate AI models for manufacturing applications such as manufacturing parameter optimization, quality or defect prediction, and in-process monitoring.
• Collaborate with industrial partners to identify challenges in manufacturing and leverage ORNL’s fundamental R&D capabilities to implement AI-driven solutions.
• Advance materials informatics and AI-powered process optimization to enhance sustainable material selection and manufacturing workflows.
• Work with multidisciplinary teams to align ORNL’s research goals with industry needs, particularly in domestic supply chain, biomanufacturing, and industrial decarbonization.
• Lead and contribute to proposal writing and project development for federal and industry-sponsored research.

• Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success.

Basic Qualifications:

• Ph.D. in computer science, mathematics, engineering, industrial engineering, chemical engineering, materials science, or a related field with a strong focus on AI applications in manufacturing.
• Experience in machine learning, data science, or computational methods applied to manufacturing and materials science.
• Strong programming skills (e.g., Python, TensorFlow, PyTorch, MATLAB) for AI and computational modeling.
• Familiarity with industrial automation, process control, digital twins, or smart manufacturing platforms.
• Knowledge of manufacturing principles, including supply chain strategies, bio-based materials, and industrial energy systems.

Preferred Qualifications:

• Experience with AI-driven optimization for material discovery, predictive maintenance, or recycling processes.
• Hands-on work in robotics, automation, or high-performance computing (HPC) for manufacturing.
• Knowledge of techno-economic analysis (TEA) and supply chain modeling.
• Experience collaborating with national labs, industry, or government agencies on sustainability-focused R&D.
• Strong communication and leadership skills to work with cross-disciplinary teams and industrial partners.