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, Mathematics, or closely related fields. • Experience conducting experimental, theoretical, or computational research. • Familiarity with mathematical modeling, data analysis techniques, or computational tools
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for further, more detailed analysis. Research areas include, but are not limited to: Incorporate resilience research [e.g., 2, 3] into extensions of the mathematical programming model underlying NIST ARC so as
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candidates for this project should have a strong background in Applied Mathematics, Engineering, Physics or other related disciplines. Full details of how to apply can be found at the following link: https
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: The Mathematical Sciences Department offers undergraduate, Master?s, and Ph.D. programs in pure, applied, and computational mathematics. Research across a variety of disciplines is strengthened through
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The candidate must have a strong background in algorithmics, optimization, and data science. In particular: Mathematical modelling: ability to formalize real-world personnel scheduling problems, including
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. Knowledge of simulation tools for wireless communication systems; experience in MATLAB/Python (or similar). Mathematical skills for conceptualisation, modelling, optimisation, and analysis of problems
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PhD Studentship: Green vs. Non-Green Innovation: The Role of Regulatory Policies and Market Dynamics
Business majors, they should demonstrate a clear interest in finance or economics. A strong quantitative background—particularly in mathematical modelling, statistical analysis, or computational methods—is
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engineering Mathematics » Applied mathematics Mathematics » Probability theory Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 24 Apr 2026 - 23:59 (Europe/Athens
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atmospheric conditions. These investigations will allow revisiting some classic experiments and exploring new, more original ones. The results will be analyzed in comparison with advanced mathematical models
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, volumetric analysis, and modeling of structural heterogeneity in biological macromolecules. Rather than only applying established workflows, you will explore new computational formulations and alternative ways