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Design Group in the Materials Science and Technology Division (MSTD), Physical Sciences Directorate (PSD) at Oak Ridge National Laboratory (ORNL). This position lives in the Alloy Behavior and Design Group
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. This position focuses on researching, designing, and deploying innovative data pipelines and readiness frameworks to tackle obstacles such as data heterogeneity, scalability bottlenecks, privacy
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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
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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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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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Postdoctoral Research Associate - Theory-in-the-loop of Autonomous Experiments for Materials-by-Desi
AI/ML surrogate models for inverse design of new materials and processes, incorporating simulated and experimental multi-modal datasets. Develop AI/ML approaches to bridge length- and time-scales in
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Group in support of the Nuclear Structure and Nuclear Astrophysics research program and the Nuclear Data effort. Major Duties and Responsibilities: Design, propose, perform and analyze experiments in
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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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, Environmental Sciences Division, Biological & Environmental Systems Science at Oak Ridge National Laboratory (ORNL). Major Duties/Responsibilities: Design experiments and perform laboratory investigations with
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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