62 data-mining-phd Postdoctoral positions at Oak Ridge National Laboratory in Postdoctoral
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Requisition Id 16779 Overview: We are accepting applications for Postdoctoral Research Associate positions in Data Science for Advanced Manufacturing that will focus on the development of next
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data science to develop new methodologies for assessing and improving the quality of components fabricated using advanced manufacturing processes. This position resides in the Manufacturing Systems
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magnets, batteries, and semiconductors from mined resources and electronic waste, as well as separations for bioenergy applications. Develop new research directions and contribute to proposals for external
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harsh environment applications. Develop data acquisition and control systems that include hydraulic or pneumatic actuation and pressure monitoring combined with interrogation of optical fiber-based
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methodologies as well as subsized mechanical testing methodologies on highly irradiated materials (either using ions or research reactor irradiation data) for establishing performance envelopes for materials
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fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in mechanical engineering, computer science, or a related field completed within
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data and develop data-driven methods for predicting land loss and ecosystem transitions in wetland-rich landscapes of the Gulf Coast with a focus on coastal Louisiana. This candidate will directly
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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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interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Basic Qualifications: A PhD in Earth and Environmental Sciences, Ecology, Biosciences, Botany, Geosciences, or a related
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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