Requisition Id11563

Overview:

As a U.S. Department of Energy (DOE) Office of Science national laboratory ORNL has an extraordinary 80-year history of solving the nations biggest problems. We have a dedicated and creative staff of over 6000 people! Our vision for diversity equity inclusion and accessibility (DEIA) is to cultivate an environment and practices that foster diversity in ideas and in the people across the organization as well as to ensure ORNL is recognized as a workplace of choice. These elements are critical for enabling the execution of ORNLs broader mission to accelerate scientific discoveries and their translation into energy environment and security solutions for the nation.

The Multimodal Sensor Analytics group in the Electrification and Energy Infrastructure Division (EEID) is seeking a postdoctoral research associate to contribute to the development of computational imaging computer vision and image analysis algorithms for multi-modal 2D and 3D imaging systems at ORNL. In this position you will join a diverse team of scientists with expertise in material science additive manufacturing data analytics machine/deep learning and computational imaging algorithms. Specifically you will contribute to the scientific activities of the team to enable new artificial intelligence (AI) based microscopy and tomographic reconstruction capabilities. We anticipate this role to focus on new algorithm development that will occur in tight collaboration with experimental scientists to translate the algorithmic outputs to real-world systems that will be leveraged by our industrial collaborators in their state-of-the-art systems at our facilities such as Manufacturing Demonstration Facility (MDF). This is a unique opportunity to build your research profile in a collaborative setting as well as gaining experience in developing novel computational imaging algorithms that have real world impact.

Major Duties/Responsibilities:

• Research and develop new algorithms for tomography and microscopy systems at ORNL
• Develop data-driven algorithms to enable feed-back control for computation imaging systems
• Actively participate in the research activities of the team
• Present scientific results at appropriate national and international conferences publish in peer-reviewed journals
• Ensure compliance with environment safety health and quality program requirements
• Maintain strong commitment to the implementation and perpetuation of values and ethics
• Deliver ORNLs mission by aligning behaviors priorities and interactions with our core values of Impact Integrity Teamwork Safety and Service. Promote diversity equity inclusion and accessibility by fostering a respectful workplace in how we treat one another work together and measure success.

Basic Qualifications:

• A PhD in electrical engineering computer science materials science or a related field completed within the last 5 years
• Experience in development of machine learning and imaging algorithms
• A strong record of productive and creative research demonstrated by publications in peer-reviewed journals and presentations at scientific conferences

Preferred Qualifications:

• Proficiency in computed tomography (CT) reconstruction algorithm development and its industrial applications.
• Hands-on experience with machine learning including but not limited to deep learning and neural networks for handling large-scale data.
• Strong programming skills with experience in Python TensorFlow/PyTorch.
• Familiarity with microscopy and multiscale imaging.
• Prior experience in the design and implementation of computational models machine learning algorithms or similar research tools on multi-modal multiscale imaging data.
• Familiarity with cloud computing platforms and high-performance computing environments.
• Strong collaboration skills and ability to work effectively in interdisciplinary 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

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 for up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and the availability of funding.

Please submit a current curriculum vitae including a list of publications when applying for this position.

Please submit two letters of reference when applying to this position. You can 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

Benefits at ORNL:

ORNL offers competitive pay and benefits programs to attract and retain talented people. The laboratory offers many employee benefits including medical and retirement plans and flexible work hours to help you and your family live happy and healthy. Employee amenities such as on-site fitness banking and cafeteria facilities are also provided for convenience.

Other benefits include:Prescription Drug Plan Dental Plan Vision Plan 401(k) Retirement PlanLife Insurance Pet Insurance 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.

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.