Note that this project is supervised jointly with Dr. Sophie Smout, School of Biology and Dr. Beth Scott, University of Aberdeen.
Policy makers aim to reconcile human socio-economic objectives in the marine environment, and the conservation of protected/sensitive species such as marine mammals. It is increasingly clear that management must take account of the spatial complexity of ocean habitats, with boundaries including coastlines and oceanographic features and that marine species’ use of this space is complex and responsive. In order to manage conservation effectively, it is crucial not only that we describe existing distributions of these species, but we must also aim to understand the processes that drive them.
This project will develop Bayesian spatial modelling methods which are flexible, can make use of independent data/knowledge to set informative priors, and facilitate understanding of uncertainty/risk. To make model fitting feasible we will develop methods within the framework of INLA (integrated nested Laplace approximation), Rue et al. 2009) extending existing spatial modelling methods (Lindgren et al., 2011) ) where boundaries have different reflecting/absorbing properties or by considering the distribution of multiple species taking account of dependencies that might exist such as competitive interactions.
Potential applicants are encouraged to contact the Postgraduate Officer responsible for PhDs in Statistics, in advance of making a formal application. He is: Len Thomas, email [email protected]
To make a formal application, complete the appropriate online form at http://www.st-andrews.ac.uk/admissions/pg/apply/research/ (click on “Apply Now” on that page). You also need to provide the following supporting documentation: CV, evidence of qualifications and evidence of English language (if applicable). You are welcome to include a covering letter. You don’t need to provide a research proposal or a sample of academic written work. You will need to ask two referees to provide academic references for you – once you fill in their name on the form, they will be sent emails asking them to upload their references. Please note that we give serious consideration to both the stature of your referees and the remarks that they make about you. More details about the application procedure are given at http://www.st-andrews.ac.uk/admissions/pg/apply/research/
Multiple sources of scholarship funding are potentially available, including university, research council (EPSRC) and research group (CREEM). Some are open to international students, some to EU and some UK only.
Applicants should have a good first degree in mathematics, statistics or another scientific discipline with a substantial numerical component. Applicants with degrees in other subjects, such as biology, are invited to discuss their qualifications with the Postgraduate Officer. A masters-level degree is an advantage.
Further details of the application procedure are available at the university web site https://www.st-andrews.ac.uk/study/pg/apply/research/ and the school site https://www.st-andrews.ac.uk/media/school-of-mathematics-and-statistics/documents/prospective-students/st-andrews-mathsstats-pgr-info.pdf A university-level PhD prospectus is here: https://www.st-andrews.ac.uk/study/pg/prospectus/research/
Rue H., Martino S. and Chopin N.: Approximate Bayesian Inference for Latent Gaussian Models Using Integrated Nested Laplace Approximations (with discussion). Journal of the Royal Statistical Society, Series B, 71, 319–392
Lindgren, F., Rue, H. and Lindström, J., 2011. An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach. Journal of the Royal Statistical Society, Series B (Statistical Methodology), 73 (4), pp. 423-498.