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seek colleagues with research interests in any area of applied mathematics, including computational and applied mathematics, mathematical biology, modeling and analysis of complex data and physical
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About the Opportunity JOB SUMMARY The Blazek group performs research in cosmology, including both theoretical, observational, and numerical methods. We are involved in analysis of DES data and
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training in coral reef monitoring, data analysis, and research planning. A major component of the role involves developing and managing an integrated multi-stage data and metadata platform for all Southeast
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include participation in the PhLAM's BEC experiments, analysis of atomic dynamics, and the development of numerical simulations in connection with theoretical collaborations
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 6 hours ago
Preferences Data analysis experience. Special Physical/Mental Requirements Campus Security Authority Responsibilities Not Applicable. Special Instructions Quick Link https://unc.peopleadmin.com/postings/314134
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probability, stochastic modeling, scientific computing, mathematical optimization and control, numerical analysis, and relevant adjacent fields Appl Deadline: 2025/11/11 04:59 AM UnitedKingdomTime (posted 2025
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interface. - Deployment, compilation, and execution of the ECCO-Darwin model on the supercomputer - Numerical developments on the ECCO-Darwin model code - Analysis of numerical model outputs - Processing and
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evaluation of virtual sharing configurations, assessment of metering and system integration requirements, and quantitative analysis of economic, regulatory, and grid impacts. The role involves developing and
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general relativity, geometric and mathematical analysis of the Einstein equations, analytical and numerical approaches to strong-field dynamics, relativistic and mathematical cosmology, relativistic matter
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regime (extreme-value analysis). The approach may also be complemented by establishing concentration inequalities and large deviation principles