53 image-processing-postdoc positions at Oak Ridge National Laboratory in computer-science
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mechanical testing to uncover processing–microstructure–property relationships. The candidate will have opportunities to interact with multidisciplinary teams and contribute to high-impact publications and
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Requisition Id 16805 Overview: We are seeking a Computer Scientist or Engineer with a focus on Vulnerability Research who will support the Cyber Resilience and Intelligence Division in the National
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materials within the uranium fuel cycle. Research topic areas will be related to understanding the effects of material processing on chemical and physical observables and translating this understanding
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Technology Division. This position reports to the ISED Associate Laboratory Director. The Division Director will lead and manage the science, engineering, technology development, prototype manufacturing
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for Computational Sciences. They will collaborate with leading computer and computational scientists at ORNL and external collaborators in the development and application of new computational techniques specifically
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. Preferred candidates will have demonstrated success transitioning R&D concepts into prototype demonstrations, scalable technologies, operational capabilities, or production-scale processes. Preferred
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of computational scientists, applied mathematicians, and computer scientists to link models and algorithms with high-performance computing. Author peer reviewed papers for internal and external release as
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Postdoctoral Research Associate - Multifunctional Equipment Integration Energy Conversion Technology
research assignments related to energy conversion systems including: Prototype development Material synthesis and analysis Performance testing Analysis of results Preparing research publications Prepare
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time-of-flight secondary ion mass spectrometry (ToF-SIMS), scanning electron microscopy (SEM), and X-ray diffraction (XRD). Experience in data reduction of big spectroscopy, mass spectrometry, and image
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pipelines for structured and unstructured data Experience with multimodal datasets (e.g., imaging, time-series, and process data) Experience with API-based data services, workflow automation, or integration