53 image-processing-postdoc-"https:" Postdoctoral positions at Oak Ridge National Laboratory
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and Eligibility Applications will be accepted from January 7, 2026, March 1, 2026, for one position starting as early as May 4, 2026. This position will support one postdoc for two years. You must first
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properties of the above materials. Collaborate with ORNL postdocs and staff who are involved in structural characterization. Participate in the development of new ideas and projects. Present and report
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, pyrometry, spectroscopy, co-axial and off-axis high speed imaging, and more) for process monitoring and diagnostics. Develop and implement data acquisition, signal processing, and data analytics frameworks
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compliance, reproducibility, and interoperability across scientific domains. By improving data readiness processes, this role will amplify the potential of AI-driven discovery in areas such as high energy
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physical characterization techniques (differential scanning calorimetry, dynamic light scattering, small angle neutron and/or x-ray scattering) to characterize the DIBs; and (3) Develop/implement image
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-resolution microscopy, and in situ neutron or X-ray scattering and tomography methods. Strong background in computational and image-processing software, scientific programming, and high-performance computing
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, 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: A PhD in
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relevance to clean energy, climate resilience, and infrastructure planning. Postdocs benefit from access to world-leading high-performance computing facilities and a deeply interdisciplinary research
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to contribute to development of alloys with desirable advances in mechanical properties, thermal/electrical properties, and processability. A background in solidification processing, high pressure die casting
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on designing system software for automating processes such as intelligent data ingestion, preservation of data/metadata relationships, and distributed optimization of machine learning workflows. Collaborating