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programming (C++, MPI, CUDA/HIP/ROCm). Preferred Qualifications: Familiarity with LLVM/MLIR development and multi‑language IR ecosystems. Background in formal methods or automated reasoning. Experience with
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. Scalability of Preprocessing Pipelines: Design and implement automated, parallel preprocessing workflows capable of handling multi-petabyte datasets efficiently while reducing throughput bottlenecks. Data
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(ORNL). As a postdoctoral fellow, you will produce publishable results at a steady pace and work at the interface of neutron imaging, computational modeling, and workflow automation. Applicants with
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on designing system software for automating processes such as intelligent data ingestion, preservation of data/metadata relationships, and distributed optimization of machine learning workflows. Collaborating
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techniques; and (3) developing advanced methods for inelastic neutron scattering data analysis and workflow automation. The postdoctoral researcher will work in close collaboration with Dr. Raphaël Hermann and
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/device models into open-source software tools for integrated system dynamic and transient simulations. Integrate post-processing measures for simulations to help with automation. Deliver ORNL’s mission by
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automated fiber placement Apply advanced constitutive material models for polymer composite behavior under processing conditions Collaborate with multidisciplinary research teams on simulation, manufacturing
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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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through model–experiment validation workflows. Develop and implement advanced data analysis methodologies, automated processing tools, and reproducible workflows to generate validated, publication-quality
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applying machine learning for materials and/or process discovery, particularly quantum and/or microelectronic materials Expertise in using or developing agentic tools for automation of scientific discovery