Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
mathematics, mathematical statistics, probability, data analysis, longitudinal modelling, mixed models, or computational methods. Literature LaMotte, L. R. Foundations of Multiple Regression and Analysis
-
framework provides a unified formulation of physical processes across multiple scales. The research work will be structured around three main tasks: Mathematical modelling of coupled THMC processes within a
-
This interdisciplinary PhD project will bring together mathematics and ecology to assess the risk of invasive tree pests being transported into Great Britain by wind. While biosecurity measures largely focus on trade
-
PhD-studentship in Applied Mathematics / Quantitative Ecology: Wind‑Assisted Dispersal of Insect Tree Pests: An Interdisciplinary Modelling and Ecological Study Award Summary 100% home fees covered
-
unified formulation of physical processes across multiple scales. The research work will be structured around three main tasks: Mathematical modelling of coupled THMC processes within a consistent
-
frequencies in populations, regardless of their adaptive content. The PhD student will develop a theoretical framework in which multiple inversions, each with its own explicit genetic content, interact within
-
-resolution drought prediction system. The topic of this PhD position is the monitoring and prediction of droughts on national scale. The PhD student will develop a novel model-based drought index combination
-
insights. Information Statistical modelling of multiple omics datasets is a lively and rapidly developing research area. Ongoing technological advances make it possible to measure multiple biological data
-
models and Bayesian approaches to tackle complex, real-world data? Join this PhD project to build dynamic models and study cognitive variability using ecological momentary assessment (EMA). Join us We are
-
, such as heterogeneity of data sources and communication constraints. By leveraging tools from statistical signal processing, machine learning, optimization, and mathematical modeling, the project aims