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Postdoctoral Research Associate who will focus on creating innovative artificial intelligence algorithms for the trusted visualization of large-scale 3D scientific data. This position resides in the Data
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length scales Develop machine learning algorithms to support process optimization, predictive modeling, and intelligent manufacturing control Integrate simulation tools with in-situ sensor data from
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Application-driven Composable Distributed Storage. The candidate will be able to make research contributions in understanding and efficient use of distributed data storage and I/O subsystems for High
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comparative research across Mojo, Julia, Rust, and vendor toolchains. Basic Qualifications: Ph.D. in Computer Science, Computer Engineering, or related field. Experience with LLMs or agentic AI frameworks
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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
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strengths in high-performance computing, system architecture, and data analytics with applications in a large variety of science domains. NCCS is home to some of the fastest supercomputers and storage systems
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ferroelectric and ferroelastic materials, under external stimuli such as electric fields, light, strain, and temperature. This position resides in the Data Nanonanalytics (DNA) Group within the Nanomaterials
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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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challenges and conduct the research needed to accelerate the delivery of solutions to the marketplace. The Radiation Transport and HPC Methods (RTHPCM) Group within the Nuclear Applications Methods and Data
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will involve designing beam dynamics experiments, measurement, simulation, and data analysis. This position resides in the Accelerator Physics Group in the Accelerator Science and Technology Section