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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 7 days ago
the computational work. Researchers in the group have experience with crystal plasticity using finite element and fast Fourier transform methods, fatigue indicator parameters, process modeling and machine learning
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of vaccine and therapeutic candidates currently being produced in Good Manufacturing Practice facilities for early phase clinical trials. Minimum Requirements: Education: PhD in Immunology, Data Science and/or
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and/or case-crossover analyses, and have a promising publication record. Expertise in one or more of the following areas: statistical analysis of large data sets, machine learning, data visualization
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clinical or imaging-based research. Familiarity with vascular imaging software, image post-processing, and AI/machine learning applications in clinical or imaging research is desirable. Demonstrates strong
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across learning sciences, computer science, machine learning, HCI and education research. Research Role Research themes for the NTO Postdoctoral Associate include, but are not limited to: Developing
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, pharmacological and chemogenetic experiments in rodents to delineate mechanisms underlying drug abuse. Conduct conditioned place preference, and learning and memory tasks, intracerebral infusions, and
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therapeutics and antimicrobial peptides. The Postdoctoral Researcher will apply computational modeling, structural analysis, and machine learning approaches to support mechanistic studies of cellular signaling
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. • Expertise in one or more of the following areas: statistical analysis of large data sets, machine learning, data visualization, and a high level of independence with a publication record to support these
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Landscape analysis and modeling, with a focus on training and application of predictive machine learning tools. This researcher will synthesize regional-scale remote sensing imagery and ecological monitoring
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models