We have 15 Applied Statistics PhD Projects, Programmes & Scholarships for Non-European Students in St Andrews

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Mathematics

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St Andrews  United Kingdom

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I am a non-European student


Applied Statistics PhD Projects, Programmes & Scholarships for Non-European Students in St Andrews

We have 15 Applied Statistics PhD Projects, Programmes & Scholarships for Non-European Students in St Andrews

Hidden Markov models for spatially structured populations

  Research Group: Division of Statistics
Hidden Markov models (HMMs) offer a very powerful, flexible, and efficient structure for likelihood computation. They’re a popular tool for problems… Read more

Quantifying Trade-Offs Between Simple and Complex Models for Decision-Making

  Research Group: Division of Statistics
Policy-makers in conservation and health frequently rely on relatively simplistic statistical models to inform their decisions. There are good reasons for this. Read more
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Estimating spatial and temporal patterns in density of harbour porpoises in the North Sea using datasets from passive acoustic ocean observation networks with data flow to EU Digital Twin Ocean database

  Research Group: Centre for Research into Ecological and Environmental Modelling
A fundamental question in animal ecology is how and why the abundance of populations changes with space and time. Estimates of abundance are also critical for monitoring the conservation status of populations. Read more

Exploring synergies between statistical ecology and statistical genomics

  Research Group: Division of Statistics
While superficially different, these two areas of research share several questions in common (How many species? How many of each species? How are the species distributed spatially? How should we sample?) that differ fundamentally only in whether the species in question are flora and fauna or nucleic acids and proteins. Read more

Propagation of uncertainty for signatures of mutational processes

  Research Group: Division of Statistics
There is a trend, especially in cancer research, to i) take a set of DNA mutations ii) cross-categorize them by patient and mutational characteristic and iii) decompose the resulting counts matrix into two sets of vectors – one set representing the mutational impact of specific mutagens and one set representing the exposure of individuals to those mutagens. Read more

Incorporating Mixture of Expert Models for Longitudinal Data with Missing and Censoring

  Research Group: Division of Statistics
Longitudinal data analysis is a powerful tool for studying changes in subjects over time. However, the presence of missing data and censoring poses significant challenges. Read more

Stochastic simulation, analysis, and inference of non-linear dynamical systems

  Research Group: Division of Statistics
This project will develop a novel framework for studying the dynamics of systems presenting oscillations and multi-stabilities. This type of dynamics is abundant in many fields and especially in molecular biology, epidemiology, ecology, sociology. Read more

Stochastic modelling and inference for live-cell gene expression time-series data to unravel the mechanisms of stem cell differentiation

  Research Group: Division of Statistics
This project will develop statistical methodology for noisy time-series data and stochastic computational models to analyse live-cell imaging data provided by the lab of our collaborator Dr Cerys Manning at the University of Manchester. Read more

Identifying complex spatio-temporal biomarkers of brain diseases

  Research Group: Division of Statistics
Bayesian models today are providing the tools to explore the complexity of brain architecture. Therefore, there is a crucial need for leading researchers with an in-depth comprehension of the current challenges in neuroscience and the quantitative skills to develop cutting-edge solutions. Read more

Statistical ‘omics on graphs

  Research Group: Division of Statistics
The field of statistical genomics (and related omics) is rapidly accepting that graphical models have a role to play in addressing the complexity of the molecular systems being investigated. Read more

Distance sampling with milder assumptions

  Research Group: Division of Statistics
Estimating animal density or abundance is a fundamental challenge in statistical ecology. Distance sampling is a widely employed method for addressing this issue. Read more
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