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Sciences and Technology Directorate (ESTD) at Oak Ridge National Laboratory (ORNL). As part of our research team, you will engage with researchers with various backgrounds such as materials science, sensing
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
Requisition Id 15685 Overview: The Center for Nanophase Materials Sciences (CNMS) is seeking a Postdoctoral Research Associate to support research directed towards developing novel AI/ML algorithms
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materials discovery, combustion chemistry, and additive manufacturing. Publish research findings in peer-reviewed journals, conferences (e.g., SC, NeurIPS, AAAI), and open-source repositories. Mentor graduate
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post-doctoral research associate to simulate amorphous materials and crystallization reactions using atomic-scale simulations. As a post-doc, you will utilize high performance computing and rare event
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these documents directly to your application or have them sent to postdocrecruitment@ornl.gov with the position title and number referenced in the subject line. For full consideration, please submit materials by
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and number referenced in the subject line. For full consideration, please submit materials by November 1, 2025. About ORNL: As a U.S. Department of Energy (DOE) Office of Science national laboratory
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national security, proliferation detection, and nuclear forensics applications. This position resides in the Collection Science and Engineering Group in the Material Characterization and Modeling Section
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leadership class Computing Facilities (LCFs). The successful candidate will demonstrate strong expertise and skills in computational materials, data analytics, development of surrogate and generative DL models
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chain, material flows, and development costs throughout the lifecycle of a geothermal well to identify opportunities to reduce materials, time, and environmental impact of geothermal wells. Help support
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applications. You’ll help design, train, and evaluate AI systems that plan, reason, and take actions to accelerate scientific discovery across domains (materials, chemistry, climate, fusion, biology, and more