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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
of excellence for outbreak analytics and disease modeling, named Insight Net. This position’s efforts will focus on developing predictive and analytic models of infectious disease and will use dynamic models and
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permafrost regions. By combining field data with mathematical and physical modeling, this international project aims to advance our understanding of the impacts of permafrost thaw beyond ecological tipping
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development programs. The Office of Fusion Energy Sciences (FES) has four strategic goals: (1) Advance the fundamental science of magnetically confined plasmas to develop the predictive capability needed for a
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At the Digital Twin Innovation Hub, we are developing infrastructure for the construction, simulation, analysis, and visualization of a human immune system model that represents the majority of immune cell
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of tools for mathematical model correlation / cross-checks between analytical predicted and experimentally identified modes, deflections, strain Participate in the development and application of the Agency's
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biological samples. By controlling the physical interface between biology and measurement, we aim to generate structured, high-quality datasets that enable rigorous quantitative analysis and predictive
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Transferability, as well as Deep Learning for Complex Structures. These novel methods will be applied to practical tasks such as predicting European water storage, quantifying permafrost thawing, sea level budget