13 image-processing Postdoctoral positions at Oak Ridge National Laboratory in computer-science
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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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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
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advanced manufacturing processes. This position resides in the Deposition Science and Technology Group in the Manufacturing Science Division (MSD), Energy Science and Technology Directorate (ESTD) at Oak
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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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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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advanced manufacturing processes. This position resides in the Deposition Science and Technology Group in the Manufacturing Science Division (MSD), Energy Science and Technology Directorate (ESTD) at Oak
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opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: PhD in chemical engineering, chemistry, mechanical engineering, civil
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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