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Sustainable Systems Section, Environmental Sciences Division, Biological & Environmental Systems Science at Oak Ridge National Laboratory (ORNL). Major Duties/Responsibilities: Design experiments and perform
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research methods on large, domain-specific scientific datasets. Major Duties/Responsibilities: Designing and developing foundational AI-driven techniques for the generation and exploration of complex, large
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Preferred Qualifications: We are interested in candidates with general research experiences in quantum optics and quantum information science. Priority is given to candidates with experience on the design
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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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a particular emphasis on error-corrected methods for future fault-tolerant quantum computing. The algorithms will be designed to address key models of quantum materials, such as the Hubbard model
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domain experts—such as those in neutron scattering and urban science—to apply and evaluate research methods on large, domain-specific scientific datasets. Major Duties/Responsibilities: Designing and
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, finite volume, and machine learning to solve challenging real-world problems related to structural materials and advanced manufacturing processes. The successful candidate will have experience with
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characterization of HPC and scientific AI applications or libraries on multi-tier HPC storage systems. Design and evaluation of approaches for time-sensitive or data-intensive processing of data originating
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a
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physics (HEP) detectors, neuromorphic computing, FPGA/ASIC design, and machine learning for edge processing. The successful candidate will work with a multi-institutional and multi-disciplinary team