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supported by an individualized mentorship structure designed to foster scientific independence and career advancement. Prior trainees from this program have gone on to successful careers in both academia and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
emphasis is not just on data science majors but on all students becoming data literate. The school’s culture has an open and transparent structure, governance, and business model. Position Summary Dr. Jun
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candidate will work on an exciting project focused on extracting and analyzing experimental and computational data to develop predictive models for polymer-based materials. This project aims to leverage
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Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical
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Applications are invited for a Postdoctoral Research Associate with expertise in optical spectroscopy, structural characterisation techniques and modelling applied to next-generation semiconductors
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for Resilient Water Systems Position Summary: We are seeking a highly motivated and interdisciplinary Doctoral Research Assistant to join a collaborative project aimed at advancing understanding of sediment
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Requisition Id 15537 Overview: We are seeking a Postdoctoral Research associate in computational nuclear physics. This position focuses on nuclear theory with an emphasis on nuclear structure and
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. The goal is to quantify both the extent of material degradation and its precise spatial distribution within the battery structure. By modeling the battery as a dynamic 3D acoustic landscape, we expect to be
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. Advance Bayesian and ensemble learning approaches for non-stationary temporal processes. Implement probabilistic diffusion or generative models for long-term forecasting. Collaborate closely with
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
related discipline with a focus on Digital Twins, AI, ML, or smart infrastructure systems. Strong background in computational modeling, data analytics, and/or automation in construction or infrastructure