18 operations-optimization Postdoctoral research jobs at Oak Ridge National Laboratory
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seeking to fill a Postdoctoral Research Associate position to work in the areas of environmental life cycle assessment (LCA), technoeconomic optimization; and industrial energy efficiency and production
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guarantees while minimizing performance impact. Additionally, you will optimize the balance between privacy and utility, addressing the challenges of heterogeneous privacy budgets and varying requirements
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physics (HEP) detectors, neuromorphic computing, FPGA/ASIC design, and machine learning for edge processing. The successful candidate will work with a multi-institutional and multi-disciplinary team
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optimization, and application-driven performance analysis for HPC, scientific Artificial Intelligence (AI), and scientific edge computing. We are a leader in computational and computer science, with signature
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-building energy performance and systems integration, deployment, and analysis in support of the DOE mission. Staff members lead and participate on teams focused on R&D and deployment of energy-efficient
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Requisition Id 15553 Overview: We are seeking a Postdoctoral researcher in data quality assessment and control and sensor network optimization who will focus on R&D of sensor network design. This
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techniques to enhance model quality, resource optimization, and adaptive execution in diverse workflows. Investigate strategies to balance performance and resilience across heterogeneous computational
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seeking a postdoctoral researcher with expertise in data management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making
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the Manufacturing Science Division (MSD), Energy Science and Technology Directorate (ESTD) at Oak Ridge National Laboratory (ORNL) to work in the areas of life cycle energy impacts analysis, technoeconomic analysis
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liquids, frustrated magnetism, excitonic magnets, and strongly correlated electron systems. You will work closely with theorists, experimentalists, and computer scientists to build robust, scalable