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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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engineering, chemical engineering, and automation. The successful candidate will support research in a variety of areas and support staff in publishing original peer-reviewed research articles. Major Duties
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workflows to enable AI-readiness at scale. You will work on designing system software for automating processes such as intelligent data ingestion, preservation of data/metadata relationships, and distributed
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to convey their requirements for I/O performance and data atomicity, consistency, durability, and retention. Intelligent and automated selection and composition of data and storage service capabilities and
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detection, predictive modeling, process optimization, and automated decision support, including real-time and edge deployment Collaborate with multidisciplinary teams to provide sensing, computational, and
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researcher to join the Workflow Systems Group and help advance the use of AI in scientific discovery. This position centers on scientific machine learning, automated AI/ML optimization, and high-performance
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following areas: automated controls, SLAM, autonomous navigation, or trajectory planning. Experience integrating hardware, deploying, and evaluating algorithms on physical robots. Proficiency in Python
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analysis, modeling, or automation using tools such as Python, MATLAB, C#, C++, or similar engineering software environments. Experience with CAD/CAM/CAE tools such as Siemens NX, SolidWorks, Mastercam
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system dynamic and transient simulations. Integrate post-processing measures for simulations to help with automation. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our
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of distributed-memory systems and many‑core architectures. Preferred Qualifications: Formal Methods: Experience with automated reasoning or verification tools (e.g., Z3, TLA+, LEAN) to ensure correctness