Applications are welcomed for students wishing to undertake a PhD in
Statistics at St Andrews. Full funding (fees, plus stipend of approx.
£14,700) is available for well-qualified students; we encourage
applications as soon as possible to maximize your chances of being
funded. UK, EU and other overseas students are all encouraged to apply.
New PhD students would typically start in September 2019, but this is
flexible.
Members of the Statistics Division at St Andrews are particularly active
in the fields of statistical ecology. Other research topics include
Bayesian statistical inference, computer-intensive inference, data
mining, data smoothing, latent state models and experimental design.
Lastly, we have a growing statistical medicine and molecular biology
group.
General applications from potential students interested in these areas
are welcome. In addition, we are looking for candidates for the
following specific projects; more details of these, the PhD environment
and the application process are at the following web site:
http://tinyurl.com/StAndStatsPhD (pdf document; full address
http://www.st-andrews.ac.uk/media/school-of-mathematics-and-statistics/documents/prospective-students/st-andrews-statistics-phd-opportunities.pdf).
Specific projects (supervisor in brackets):
• Spatial capture-recapture methods for snow leopards (David Borchers,
Richard Glennie and Koustubh Sharma (Snow Leopard Trust))
• Modelling wildlife distribution in continuous space and time (David
Borchers)
• Acoustic spatial capture-recapture methods (David Borchers)
• Object classification from mobile and static sensor feeds (Carl Donovan)
• Estimating numbers of molecular ‘species’ in a tissue (Andy Lynch and
Hannah Worthington)
• Statistical underpinnings of mutational signature analyses (Andy Lynch
and Michail Papathomas)
• Modelling the interface of metabolism, methylation and mitochondria in
prostate cancer (Andy Lynch)
• Methods to model telomere length dynamics in a model organism (Andy
Lynch and Heler Ferreira (School of Biology))
• Statistical design and inference for single cell gene expression data
(Giorgos Minas and Andy Lynch)
• Stochastic modelling of populations of interacting cells with complex
underlying phenotypes (Giorgos Minas, Tomasso Lorenzi and Mark Chaplain)
• Bayesian identifiability for log-linear models (Michail Papathomas)
• Modelling population dynamics from detection survey data (Len Thomas
and Richard Glennie)
In addition, we are offering the following project in collaboration with
other Schools within the Centre for Biological Diversity; note that the
primary supervising school is not Mathematics and Statistics.
• The influence of body condition on functional behavioural decisions of
animals (Nathan Bailey (Biology), Patrick Miller (Biology) and Len Thomas)
For informal discussion about any aspect of the above, contact Prof. Len
Thomas <[log in to unmask]>.
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