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Fully funded PhD studentship on Bayesian nonparametric models
jueves, 31 de marzo de 2016

Fully funded PhD studentship on 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.

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 are available at

This award is a Graduate Teaching Assistantships (GTAs) and includes PhD fees and a scholarship of £14,296 per year for 3.5 years. Students engaged as Graduate Teaching Assistants hold a unique position in the University in that they are both registered students in receipt of a scholarship award and employees of the University. Teaching duties may include: marking, demonstrating, tutoring and outreach. The School expects that GTAs will do no more than six hours of teaching and teaching-related duties including preparation per week during term-time.

The deadline for applications is 16th May 2016.

Interviews for this position will be held at the University of Kent on 26th May 2016. If it is not possible to attend in person interviews can be conducted via Skype.