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Field
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
modeling of large-scale dynamics in networks. This role involves creating large scale models of dynamic phenomena in electrical power networks and quantifying the risk of rare events to mitigate
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. Integrate deep mutational scanning data to assess viral fitness and immune escape, collaborating with experimental virologists. Work with large-scale genomic and proteomic datasets from BV-BRC, GISAID, and
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for interacting with colleagues and stakeholders. Department Specifics Develop various machine learning and data mining models including convolutional neural networks (CNNs), Transformers, large language models
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modify and develop new procedures to achieve research goals. Moreover, the incumbent will collect, process, and analyze field and laboratory data and help coordinate data collection and logistics. 60% (E
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analyzing publicly available data on employment, education and higher education residing in large federal data sets (e.g., Census data, NCES data). Conducts research and prepares project-related technical
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spirit. UT Austin, recognized by Forbes as one of America’s Best Large Employers , provides outstanding employee benefits and total rewards packages that include: Competitive health benefits (employee
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, the incumbent will collect, process, and analyze field and laboratory data and help coordinate data collection and logistics. 60% (E) Research and Informal instruction Perform experiments planned in the different
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and cellular biology, assist in sorting platform development, perform molecular and in vivo characterization of sorted cells, analyze large-scale bioinformatics datasets to identify novel cell subsets
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that address real-world challenges and deliver positive business outcomes. The Institute for Insight is equipped with a computer cluster that includes multiple GPUs, designed for big data analytics for both
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laboratories The candidate will also have immediate access to brain PET data acquired from multiple universities, including Stony Brook. This includes large (>30 participants) datasets examining