12 postdoctoral-image-processing Postdoctoral positions at Oak Ridge National Laboratory
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Requisition Id 17093 Overview: The Plant-Soil Interactions Group within the Environmental Sciences Division (ESD) at Oak Ridge National Laboratory (ORNL) seeks a postdoctoral researcher in Coastal
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Postdoctoral Researcher in the fields of uranium chemistry and nuclear forensics. The role entails performing and leading cutting-edge research on nuclear fuel cycle-related materials with a focus on solid
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Requisition Id 17102 Overview: We are seeking a postdoctoral researcher who will focus on the development and application of separation techniques and fusion materials performance assessment
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Postdoctoral Research Associate - Multifunctional Equipment Integration Energy Conversion Technology
Requisition Id 16999 Overview: We are seeking a Postdoctoral Researcher who will focus on conducting, coordinating, and reporting complex research assignments related to advanced thermal and energy
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disturbance at scale. A cohort of postdoctoral researchers will be hired across multiple institutions to collaboratively support scientific advances guided by AI/ML, remote sensing, process-based modeling
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Requisition Id 17107 Overview: We are seeking a postdoctoral researcher focused on the development of in situ interfacial characterization techniques for silicon-based materials and to map
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Requisition Id 17038 Overview: We are seeking a Postdoctoral Research Associate with a strong background in organic synthesis and coordination chemistry to develop novel chelation platforms for s
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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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Requisition Id 16296 Overview: We are seeking a Postdoctoral Research Associate to develop AI-driven automation workflows for aberration-correction scanning transmission electron microscopy (STEM
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Requisition Id 16704 Overview: We are seeking a Postdoctoral Research Associate who will focus on AI-enabled plant ecophysiology to improve mechanistic understanding and predictions of ecosystem