Postdoc Research Associate - Machine and Deep Learning, Computer Vision, and Computational Imaging

Requisition Id 11563 

Overview: 

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an extraordinary 80-year history of solving the nation’s biggest problems. We have a dedicated and creative staff of over 6,000 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 ORNL’s 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 ORNL’s 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