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for Computational Sciences. They will collaborate with leading computer and computational scientists at ORNL and external collaborators in the development and application of new computational techniques specifically
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integration of novel computer architectures for advanced edge computing scenarios. The research involves design space exploration and the implementation of digital systems using FPGAs, with potential for future
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members Sriram Pemmaraju and Sourya Roy on sampling problems in the distributed and parallel computing setting. The ideal candidate will have research experience in sampling algorithms and related areas
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their data pipeline. These foundation models will be used to improve the operation of cryoSTEM microscopes when applied to biological samples. Parallel Model Training: Deploy parallel computing systems
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used to improve the operation of cryoSTEM microscopes when applied to biological samples. Parallel Model Training: Deploy parallel computing systems for training large-scale cryoSTEM foundation models
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between the severity of joint damage and the severity of symptoms. These parallels make naturally-occurring equine OA a powerful population for developing pain measures that can translate to humans. As such
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cellular mechanisms that maintain sensory system homeostasis, and how disruptions in these processes contribute to sensory dysfunction. The lab employs a broad range of techniques – including viral tracing
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Model. In parallel, the group is engaged in hardware activities related to the development and implementation of new FPGA-based trigger processors, both for the operation of the ATLAS muon spectrometer
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empirical evidence. The project runs for 33 months and comprises three research components operating in parallel, each led by a postdoctoral researcher and integrated through monthly team meetings and
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of computational scientists, applied mathematicians, and computer scientists to link models and algorithms with high-performance computing. Author peer reviewed papers for internal and external release as