40 computational-intelligence Postdoctoral research jobs at Oak Ridge National Laboratory
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breeding blankets, including computational fluid dynamic (CFD), thermal hydraulic, and magnetohydrodynamic (MHD) analyses. We seek individuals with advanced analytical and computational skills who can use
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science, computer science, computer engineering, electrical engineering, and optical engineering, and frequently collaborates with partners in industry, academia, and other government organizations
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visual representation and analysis of large-scale 2D/3D scientific data. This position resides in the Data Visualization Group in the Data and AI Systems Section, Computer Science and Mathematics Division
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Requisition Id 15217 Overview: The Multiscale Biomedical Systems group in the Advanced Computing in Health (ACH) section in Computational Sciences and Engineering Division (CSED), Computing and
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testing program. Security, Credentialing, and Eligibility Requirements: For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant form of identification will be required. Additionally
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to communicate research results through reports, publications and presentations. Experience in accelerator physics, including working in a control room, conducting accelerator-based experiments, and computational
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independently within a supportive group setting. Ensure compliance with environment, safety, health and quality program requirements Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with
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intelligence techniques for scientific workflows deployed across heterogeneous computing resources. As a postdoctoral fellow at ORNL, you will join a dynamic team of researchers specializing in workflow
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companies participating in the DOE’s Better Plants program. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service
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at the intersection of quantum information science and fundamental materials physics. The research program focuses on understanding the fundamental limits of spin-based quantum sensors as probes of magnetic and