29 phd-position-in-data-modeling Postdoctoral positions at Oak Ridge National Laboratory
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
that can incorporate multi-scale computational simulations to aid with data fusion across multiple modalities of experiments with the final goal of discovering novel materials phenomena or even new materials
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framework for driven and open quantum systems. Phenomenological modeling of dynamics/transport behaviors in complex systems, including strongly correlated electron systems. Experience in analyzing data from
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related experimental data. This position resides in the Neutron Scattering Division, Neutron Sciences Directorate at Oak Ridge National Laboratory (ORNL) and is embedded in the MAIQMag (Multimodal AI
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methods to work with a team of scientists in CSD to model chemical reactions important to determine the longevity of amorphous materials. That mechanistic information will be incorporated into process-based
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develop cutting-edge differential privacy techniques for large-scale models across multiple institutions. This position offers a unique opportunity to work with the world's first exascale system
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reactions, as well as nuclear data. The position is part of the nuclear physics team that resides in the Advanced Computing for Nuclear, Particle, and Astrophysics group at the National Center
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our growing research team. These positions focus on developing next-generation AI and high-performance computing (HPC) methods for computational imaging and spatiotemporal data analysis. We
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materials that may serve as model systems displaying quantum behaviors. It will also provide opportunities for collaboration with quantum computing efforts within the Quantum Science Center, guiding and
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Department of Energy (DOE). ORNL’s CCP conducts world-class research and development in multi-scale computational coupled physics, large scale data analytics and DL, and model-data integration at the DOE’s
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characterization, and predictive fault tolerance in HPC systems. Architectural exploration and performance modeling of high-bandwidth memory (HBM) and DDR memory systems in the context of data-intensive scientific