[Forum SIS] Fully funded Vice-Chancellor’s PhD studentship on Bayesian nonparametric models for the study of migration patterns of UK bird populations

[Alessio Farcomeni]

With apologies for cross-posting...

*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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