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

Requisition Id 15490 

­­Overview:  

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.

Major Duties/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. Promote equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success.

Basic Qualifications:

• 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.

Preferred Qualifications:

• 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.

Special Requirements:

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. Initial appointments and extensions are subject to performance and availability of funding.

Please submit three letters of reference when applying to this position. You may upload these directly to your application or have them sent to Postdocrecruitment@ornl.gov with the position title and number referenced in the subject line.

Instructions to upload documents to your candidate profile:

• Login to your account via jobs.ornl.gov
• View Profile
• Under the My Documents section, select Add a Document

Security, Credentialing, and Eligibility Requirements:

For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant form of identification will be required.  Additionally, ORNL is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as mandated by Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which requires a favorable post-employment background investigation.

To obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background check investigation.  This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year.  This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.

For foreign national candidates:

If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment.  Once you meet the three-year residency requirement, you will be required to obtain a PIV credential to maintain employment.  

About ORNL:

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.

ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience.

Other benefits include the following: 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, and Employee Discounts.

If you have difficulty using the online application system or need an accommodation to apply due to a disability, please email: ORNLRecruiting@ornl.gov or call 1.866.963.9545.

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This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply.  UT-Battelle is an E-Verify employer.