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PhD position at Kent University: Bayesian nonparametric models for the study of migration patterns of UK bird populations. Forumgrstats

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Λέσχη Φίλων Στατιστικής - GrStats forum
PhD position at Kent University: Bayesian nonparametric models for the study of migration patterns of UK bird populations. Forumgrstats
Λέσχη Φίλων Στατιστικής - GrStats forum
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PhD position at Kent University: Bayesian nonparametric models for the study of migration patterns of UK bird populations. Empty PhD position at Kent University: Bayesian nonparametric models for the study of migration patterns of UK bird populations.

Fri 1 Apr 2016 - 9:56
Project title: Bayesian nonparametric models for the study of migration patterns of UK bird populations.

This is a collaborative project between the University of Kent and the British Trust for Ornithology (BTO) which was awarded a prestigious Vice-Chancellor studentship through a Sciences Faculty Competition.

Supervisory team: Dr Eleni Matechou (University of Kent), Dr Alison Johnston (BTO), Professor Jim Griffin (University of Kent)


Project description
Many bird species breed in the UK and migrate to spend the winter in Africa. These migration patterns can change from year-to-year (for example, climate change has been linked to earlier migration) and can lead to changes in demographic parameters such as phenology, population or the distribution of species. It is of paramount interest to study these changes and their effect on wildlife populations to assess the need for or effect of conservation strategies to support species that are endangered or in decline. A large data set of bird species that breed in the UK and spend the winter in Africa has been collected by the British Trust for Ornithology (BTO) as part of the Constant Effort Sites (CES) monitoring scheme.

The main supervisor, Dr Eleni Matechou, has demonstrated the importance of studying migratory wildlife populations using Bayesian nonparametric models to estimate key demographic parameters. Nonparametric models do not have a fixed number of parameters and their complexity can adjust to the data rather than being fixed by a researcher. Bayesian nonparametric methods provide us with ways to set priors for unknown and potentially infinite dimensional objects (such as distributions or functions) and can be estimated using Markov chain Monte Carlo methods to obtain posterior summaries of quantities of interest. The flexibility of these methods to accurately model complex data in many application areas such as linguistics, finance and genetics has led to a large and vibrant community of researchers working on these methods.

In this collaborative interdisciplinary project, you will develop further these ideas and use novel and sophisticated statistical models, using Bayesian nonparametric methods, to understand patterns of bird migration within the UK. The results will be used to inform conservation management strategies. The supervisory team (Dr Eleni Matechou, Dr Alison Johnston and Professor Jim Griffin) have experience of Bayesian nonparametric methods and the modelling of animal populations. The project deals with issues, eg. climate change and its effect on wildlife populations, that are of worldwide concern and will involve state-of-the-art statistical methods which are of interest both in the academic world and in industry.

Further details and information on funding are available at https://www.findaphd.com/search/ProjectDetails.aspx?PJID=74130

Application deadline: 16th of May 2016


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