Postdoctoral Research Associate - ML & CI for Sparse & Multi-Modal Computed Tomography

Oak Ridge National Laboratory • Oak Ridge, TN

76d

About The Position

The Multimodal Sensor Analytics group in the Electrification and Energy Infrastructure Division (EEID) is seeking a postdoctoral researcher with proven expertise in computed tomography (CT) reconstruction, including sparse-view and limited-angle algorithms, and the application of advanced machine learning (ML) and computational imaging methods to scientific and industrial imaging data. You will directly contribute to developing and deploying algorithms for multi-modal tomography (X-ray, neutron, and electron), advancing methods for non-destructive evaluation (NDE) and scientific imaging. This position emphasizes bridging cutting-edge ML/AI with real-world imaging systems in collaboration with experimental scientists, leveraging facilities such as the Manufacturing Demonstration Facility (MDF). This role offers a unique opportunity to drive impactful research on sparse scientific imaging while building a strong research profile in computational imaging and ML for CT.

Requirements

• Ph.D. in electrical engineering, computer science, or related discipline completed within the last five years.
• Demonstrated expertise in computed tomography (CT), with experience in sparse-view and/or limited-angle reconstruction and published research in this area.
• Experience applying ML/AI algorithms to scientific imaging data (e.g., CT, microscopy, multi-modal datasets).
• A strong record of productive and creative research, demonstrated by peer-reviewed publications and conference presentations.

Nice To Haves

• Hands-on experience with ML/AI frameworks (PyTorch, TensorFlow) for tomographic reconstruction and analysis.
• Familiarity with physics-informed, plug-and-play (PnP), or generative models for imaging.
• Prior experience with multi-modal tomography (X-ray, neutron, electron).
• Knowledge of high-performance computing or cloud environments for large-scale data.
• Strong collaboration skills and ability to work in interdisciplinary teams.

Responsibilities

• Lead research on sparse-view and limited-angle CT algorithms for scientific and industrial applications.
• Develop and apply ML/AI-driven computational imaging methods (e.g., deep learning, implicit neural representations, diffusion models) for CT reconstruction, enhancement, and defect detection.
• Advance algorithms for multi-modal tomography (X-ray, neutron, electron).
• Collaborate with experimentalists to validate methods on real-world systems.
• Publish in high-impact journals and present at leading national and international conferences.
• Ensure compliance with environment, safety, health, and quality program requirements.
• Uphold strong values and ethics in collaborative research.
• Deliver ORNL's mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service.

Benefits

• Medical and retirement plans
• Flexible work hours
• On-site fitness, banking, and cafeteria facilities
• 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

What This Job Offers

• Career Level: Entry Level
• Industry: Professional, Scientific, and Technical Services
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees