Postdoctoral Research Associate - Data Science for Advanced Manufacturing

About the role

We are accepting applications for Postdoctoral Research Associate positions in Data Science for Advanced Manufacturing.

Responsibilities

• Develop and integrate imaging and other sensing modalities for data collection and monitoring in manufacturing environment
• 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 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

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 manufacturing environment

Proficiency in Python and common data science and machine learning libraries (e.g., NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow)

Ability to present complex results to multidisciplinary teams, including engineering, scientific, and operational stakeholders

Excellent verbal and written communication skills

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

Excellent written and oral communication skills

Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory

Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs

Skills

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

Benefits

UT-Battelle is an E-Verify employer