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institute and would be encouraged to find ways to thrive and grow their own research program. This position is Boston-based and is available through grant funding that runs until August 31, 2026
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an exciting approach to agentic, fully autonomous thin film development using a combination of automated electroplating, in-operando measurements, and AI driven algorithms. He or she will work with a team of
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Cornell University, Information Science Position ID: Cornell -IS -POSTDOC [#29666] Position Title: Position Location: Ithaca, New York 14850-4623, United States of America [map ] Subject Area
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 14 days ago
++, taking advantage of Spark, Hadoop, and other tool stacks as appropriate. * Developing computational and algorithmic approaches to understanding the neurobiological mechanism of neurodisorders. * Interact
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Apply now Job no:535376 Work type:Faculty - Pro Tempore Location:Eugene, OR Categories:Instruction, Computer and Information Science, Data Science Department: CAS CIS Computer & Information
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Posting Details Position Information Fiscal Year 2024-2025 Position Title Postdoctoral Associate (PRODiG+ Scholar), Computer Science Classification Title Postdoctoral Associate Department
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network modeling to address real-world policy challenges through algorithm development and technical analysis. Key Responsibilities Conduct original research in generative AI Train and supervise graduate
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Professor Lei Xie seek to hire Postdoctoral Research Associates to train in and oversee in interdisciplinary projects involving AI algorithm development, physiologically based pharmacokinetics, computational
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transcriptomics, flow cytometry, and murine solid tumor models. This postdoctoral position is federally funded through a T32 training grant. Thus, applicants must be US Citizens or Permanent Residents. St. Jude is
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lead efforts to develop experimental techniques using conventional and coherent imaging in the ultrafast time domain, as well as a computational framework for modeling and reconstructing images