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Field
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phenotypic, genotypic, and environmental data to build prediction models for key traits of blueberry such as flowering time, yield, and fruit quality. This position reports to Dr. Sushan Ru at Auburn
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, Chemistry or related scientific fields and experience and knowledge managing and analyzing spectroscopic data to build predictive models. The Successful candidates should be able to work independently, have
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computational science expertise. The Computational Science (CPS) Division focuses on solving the most challenging scientific problems through advanced modeling and simulation on the most capable computers
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, but also to develop approaches to prevent damage. In the project we aim to develop a numerical model to predict root growth. Your task as a Postdoc researcher is to develop a measurement and monitoring
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: Computational materials modeling: DFT, molecular dynamics, phase-field modeling, or multiscale simulations. Data-driven materials discovery: ML models for property prediction, materials design, or synthesis
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interest in social science applications, and with strong competence in statistics and machine learning. The successful candidate will develop predictive models using machine learning and work alongside other
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execution models towards designing the next-generation unified cloud stack. CloudNG has a strong emphasis on performance and performance predictability, sustainability, seamless accelerator integration, and
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(that might predict learning and outcomes), underlying cognitive and neurobiological mechanisms, and intervention outcomes using tools including, but not limited to brain imaging (broadly defined
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including applications to biology , condensed matter analogues of axions , Condensed matter theory , Cosmology , General relativity , Phenomenology , Physics Beyond the Standard Model , Physics of cold atoms
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clear, auditable explanations of assessments and predictions, ensuring analysts and operators understand model outputs in time-sensitive security scenarios. Real-time intelligence fusion and rapid