71 development-"https:"-"https:" Postdoctoral positions at Oak Ridge National Laboratory
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Requisition Id 16540 Overview: We are seeking a Postdoctoral Research Associate who will develop and apply computational methods based on electronic structure theory and artificial intelligence
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. Compose technical reports, create presentations, and publish peer-reviewed papers Support the development of new resources, training, and tools to support companies participating in the DOE’s Better Plants
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Requisition Id 16386 Overview: We are seeking a Postdoctoral Research Associate to conduct advanced research on the mechanical behavior and microstructure evolution of advanced structural alloys
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at scale. Experience in HPC and associated software development for applications, middleware, and/or system software. Flexibility to adapt to diverse R&D projects and tasks. Effective communicator in both
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Research Associate to develop, scale, and apply artificial intelligence (AI) and deep learning (DL) models for power grid systems. The successful candidate will contribute to scalable AI workflows for grid
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program, which provides research support, professional development, and social activities. Major Duties/Responsibilities: Assume a leading role in one or more of the group’s contributions to the LEGEND
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data science to develop new methodologies for assessing and improving the quality of components fabricated using advanced manufacturing processes. This position resides in the Manufacturing Systems
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hardware. As part of our team, you will perform research to develop new scalable quantum simulation algorithms, based on multi-linear representation theory, and apply them to real world applications spanning
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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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state-of-the-art high-performance computing. Key Research Areas: AI for Science: Research and development of large-scale AI models for science, focusing on pre-training, instruction-based fine-tuning, and