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: Reference Number 11340 Artificial intelligence (AI) methods, particularly generative AI, have the potential to significantly advance and transform Earth System Sciences (ESS), especially given the complexity
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: Reference Number 11336 Artificial intelligence (AI) methods have the potential to significantly advance and transform Earth system sciences, particularly given the complexity of the Earth system as a dynamic
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to the roles of elongation factors and their connection to human diseases. The successful candidate is expected to: Conduct research in computational biophysics related to the project mentioned above using
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for a full-time postdoctoral research position in Professor Henrik R. Larsson’s Theoretical Chemistry/Computational Physics group at University of California, Merced. The postdoctoral scholar will work
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on developing computational methods for designing and interpreting pooled high-throughput experiments. The work will be done in close collaboration with a larger team that integrates computational and
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will work on a DOE-funded SciDAC project Moving Electrons through Space and Time: Enabling the Quantum Dynamics of Chirality-Induced Spin Selection Through Novel and Scalable Computational Methods