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-scale scientific data. Publishing research in leading peer-reviewed journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources
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parallel computing. Demonstrated hands-on experience and understanding of developing scientific data management, workflows and resource management problems. Strong problem-solving and communication skills
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journals and conferences. Researching and developing parallel/scalable uncertainty visualization algorithms using HPC resources. Collaboration with domain scientists for demonstration and validation
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. Integrate the feed chemistry data being developed in a parallel project. Travel to India to help implement the updated model. This would be as needed and no more than two times per year. Conduct a comparative
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learning frameworks (e.g. PyTorch, TensorFlow) and relevant libraries. Practical experience inscalable data processing, including the use of parallel computing, cloud platforms,and distributed systems
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collected for various experiments and interpret to understand biology of plant-pathogen interactions Collaborate with other lab members on various projects to conduct computational analyses in parallel
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, Climate Science or a related field. Experience in earth system modeling, data assimilation, and remote sensing of land surface variables. Experience with parallel computing on high performance cluster
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) exploring the role of autologous fat and muscle cells in breast reconstruction with autologous tissue transfer. The position involves working in parallel with several different cell types, which requires
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composition, structural organization, and post-translational modifications, and play a central role in regulating biological function. In parallel, mechanical alterations are increasingly recognized as
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a new project to build a “second-generation,” tunable 2A peptide, which will involve high-throughput microscopy screening and massively parallel reporter assays. Ideal candidates will have expertise