A revolution is taking place in survey technology for wildlife monitoring, with electronic sensors replacing human detectors, and the new technology requires new partnerships between academic statisticians and industry. This 3.5 year studentship is an opportunity to work at the forefront of innovation in the conduct and analysis of high-definition video surveys of marine fauna.
We are seeking to recruit a PhD student for a 3.5 year studentship developing statistical methods for estimating density and distribution of marine fauna from digital aerial survey data. The project is a collaboration between the Universities of St Andrews and Aberdeen, Marine Scotland Science (MSS: http://www.gov.scot/Topics/marine/science/Research), and HiDef Aerial Survey Ltd. (http://www.hidefsurveying.co.uk).
The student will be associated with the Marine Alliance for Science and Technology for Scotland (MASTS: http://www.masts.ac.uk/graduate-school) Graduate Programme, and will be located in the world-leading Centre for Research into Ecological and Environmental Modelling (CREEM: http://creem2.st-andrews.ac.uk) while at the University of St Andrews. The student will spend a period of research at the University of Aberdeen and/or MSS during the PhD.
Funding covers UK/European fees plus a stipend in line with that provided by EPSRC (approx. £13,863 per annum). Applications from non-UK/EU applicants are welcomed; depending on the candidate, funding for non-UK/EU fees may be available.
The results of the PhD will help inform a strategy for digital video aerial surveys in Scotland, with the objectives of understanding how such surveys can be used for assessing the impact of human activities on the abundance and distribution of mammals and birds at sea, and to identify suitable sites for protection. The PhD will focus on methods for surveys with digital detectors (video cameras mounted on aircraft). These methods are already widely used to survey seabirds and are set to revolutionise aerial surveys of marine mammals, but statistical method development is lagging somewhat behind technological advances.
The student will develop statistical methods appropriate for such surveys, while working alongside MSS and industry collaborators to understand the biological and policy context of surveys, and to explore potential for integrating new techniques into strategic monitoring programmes. Statistical challenges include the need for methods that integrate stochastic models for diving behaviour and movement, with models for the survey process, as well as methods for dealing with uncertainty about which detections of animals are re-detections of animals previously detected on the survey (mark-recapture identity uncertainty).
Person Specification
Applicants must have, or expect to obtain at least a 2(i) Honours degree in Statistics or a closely related subject. Experience with wildlife survey methods, pattern recognition methods or hidden state models would be an advantage, as would an interest in conservation and management of marine species. The post needs to be filled by October 2015.
Contact information
For further details and an informal discussion about the project please contact Prof David Borchers, University of St Andrews, Email: [log in to unmask] Candidates should send a CV with their initial query.
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