Postdoctoral Research Associate - Data Science for Advanced Manufacturing

We are accepting applications for Postdoctoral Research Associate positions focused on the development of next-generation, data-driven manufacturing systems. This role integrates artificial intelligence, real-time sensing, and digital twins to transform how critical components are designed, produced, and qualified. The position resides in the Manufacturing Systems Analytics group within the Digital and Secure Manufacturing Section at Oak Ridge National Laboratory (ORNL).

About the role

You will work at the Manufacturing Demonstration Facility (MDF) to advance digital manufacturing technologies and accelerate their deployment to industry and national-scale applications. The MDF hosts a diverse set of advanced manufacturing systems—including powder bed, directed energy deposition, machining, polymer, and convergent manufacturing systems—used to produce critical components from advanced materials. These systems are instrumented and connected through a unified digital thread platform that captures multimodal, high-frequency data across the full manufacturing lifecycle, from process execution to post-process characterization. This environment enables the creation of high-fidelity digital twins and AI-ready datasets that support real-time monitoring, predictive modeling, and process optimization.

In this role, you will leverage large-scale, heterogeneous datasets to develop and deploy AI-driven methods for:

• Real-time quality monitoring and control of manufacturing processes
• Understanding relationships between manufacturing intent, machine behavior, and part performance
• Optimization of manufacturing processes for improved throughput, reliability, and quality

You will contribute to integrated data and AI workflows spanning data acquisition, modeling, and decision-making, including deployment at the edge and across distributed systems. You will have access to extensive experimental and computational resources and will be expected to publish research, present results, and contribute to high-impact programs. With over 100 manufacturing systems at the MDF, this role offers the opportunity to work on diverse, high-impact problems and shape the future of intelligent manufacturing.

Responsibilities

• Develop and integrate imaging and other sensing modalities for data collection and monitoring in manufacturing environments
• Develop modular, extensible workflows for data processing
• Develop and deploy data analytics, machine learning, and statistical modeling methods for multimodal manufacturing datasets, including sensor streams, in-process signals, post-process characterization data, simulation outputs, and digital twin data
• Develop, integrate, and evaluate AI/ML models for anomaly detection, predictive modeling, process optimization, and automated decision support, including real-time and edge deployment
• Collaborate with multidisciplinary teams to provide sensing, computational, and analytical expertise across projects
• Support broader research and development activities within the MDF
• Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with core values of Impact, Integrity, Teamwork, Safety, and Service
• Promote equal opportunity by fostering a respectful workplace

Requirements

• PhD in mechanical engineering, material science, electrical engineering, computer engineering, computer science, data science, applied mathematics, or a closely related field
• Demonstrated experience with multimodal data acquisition, data analytics, statistical modeling, and machine learning in a manufacturing environment
• Proficiency in Python and common data science and machine learning libraries (e.g., NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow)
• Experience developing and deploying machine learning or deep learning models
• Ability to present complex results to multidisciplinary teams, including engineering, scientific, and operational stakeholders
• Ability to work effectively in a dynamic, collaborative research environment
• Excellent verbal and written communication skills

Preferred Qualifications

• Experience working with manufacturing, materials, and sensor data
• Experience with real-time, time-series or streaming data systems and edge AI deployment
• Experience building and maintaining data processing pipelines for structured and unstructured data
• Experience with multimodal datasets (e.g., imaging, time-series, and process data)
• Experience with API-based data services, workflow automation, or integration of analytics into production systems
• Knowledge of experimental design, uncertainty quantification, scientific machine learning, or digital twin methodologies
• Experience collaborating across national laboratories, academia, or industry in multidisciplinary teams
• Motivated self-starter with the ability to work independently and participate creatively in collaborative teams
• Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever-changing needs

Special Requirements

Visa sponsorship is not available for this position. This position requires access to technology subject to export control requirements; successful candidates must be qualified for such access without an export control license. Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be up to 24 months with the potential for extension, subject to performance and availability of funding.

For employment at ORNL, a Real ID-compliant form of identification will be required. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card, which requires a favorable post-employment background investigation. This includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year (marijuana and cannabis derivatives are still considered illegal under federal law, regardless of state laws).

Three letters of recommendation are required when applying for this position.

Benefits

• Prescription Drug Plan
• Dental Plan
• Vision Plan
• 401(k) Retirement Plan
• Contributory Pension Plan
• Life Insurance
• Disability Benefits
• Generous Vacation and Holidays
• Parental Leave
• Legal Insurance with Identity Theft Protection
• Employee Assistance Plan
• Flexible Spending Accounts
• Health Savings Accounts
• Wellness Programs
• Educational Assistance
• Relocation Assistance
• Employee Discounts
• On-site fitness, banking, and cafeteria facilities