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Ecology & Conservation (statistics) PhD Projects, Programs & Scholarships

We have 11 Ecology & Conservation (statistics) PhD Projects, Programs & Scholarships

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  Protecting our seas using computers - Modelling and forecasting the expansion of a highly invasive seaweed
  Dr B Chen, Prof M Heath
Applications accepted all year round

Funding Type

PhD Type

This fully-funded 3.5 year studentship will remain open only until filled. We recommend applying immediately. In this project, you will meet with the challenge of developing an individual based model to simulate the growth and dispersal of a highly invasive seaweed (Japanese eelgrass) driven by coastal ocean currents.
  Genomic basis of extra-group paternity in the cooperatively breeding Seychelles warbler
  Dr H L Dugdale
Applications accepted all year round

Funding Type

PhD Type

Indirect genetic benefits are hypothesised to drive the evolution of extra-group paternity (EGP), yet its genomic basis is unknown.
  Why do individual Seychelles warblers age differently?
  Research Group: School of Biology
  Dr H L Dugdale, Dr A Sparks, Prof D S Richardson
Application Deadline: 31 May 2019

Funding Type

PhD Type

One of the most profound challenges we all face is our deterioration with age - a process known as senescence. Individuals clearly senesce differently, in both the age they start to deteriorate and the rate of their decline.
  What is the role of discarding in the dynamics of the demersal fish community of the Firth of Clyde?
  Dr R Cook, Dr L Clarke
Applications accepted all year round

Funding Type

PhD Type

his fully-funded studentship will remain open only until filled, and so we recommend applying immediately. The Firth of Clyde has notoriously been referred to as an ‘ecological desert’ having been intensively overfished (Thurstan and Roberts, 2010).
  Data mining for microbial adaptation to climate change - MScR in Global Environmental Challenges
  Dr G Barker
Application Deadline: 1 August 2019

Funding Type

PhD Type

About the Project. Microbes are key members of nutrient and energy cycles in all global ecosystems. Whole meta genome DNA sequencing is increasingly used to characterise microbial ecosystems and vast amounts of data are deposited in the public domain every year.
  PhD in Applied Ecology - Developing data-driven modelling in Applied Ecology
  Prof R Freckleton
Applications accepted all year round

Funding Type

PhD Type

We live in a changing world and a challenge for ecologists is to forecast how such changes will impact on natural populations. We tackle problems such as forest management, weed invasions and predicting the impacts of land management on populations of plants, insects and birds.
  Climate change impacts on New Zealand Fiordland ecosystems
  Dr A Rogers, Dr J Bell
Application Deadline: 30 May 2019

Funding Type

PhD Type

Global climate change has the potential to increase water temperatures by as much as 2.5C over the next century in some locations, with impacts on species distribution patterns, nutrient levels and primary production.
  Acoustic spatial capture-recapture methods.
  Research Group: Centre for Research into Ecological and Environmental Modelling
  Prof D Borchers
Applications accepted all year round

Funding Type

PhD Type

Many species, like gibbons, frogs, kiwi and other bird species, are difficult to see but easy to hear.
  Modelling population dynamics from detection survey data
  Research Group: Centre for Research into Ecological and Environmental Modelling
  Prof L Thomas, Dr R Glennie
Applications accepted all year round

Funding Type

PhD Type

Ecologists collect data on wild animal populations by a variety of survey methods and infer from these how the population changes over time through recruitment, survival, and movement processes.
  Object classification from mobile and static sensor feeds
  Research Group: Centre for Research into Ecological and Environmental Modelling
  Dr C Donovan
Applications accepted all year round

Funding Type

PhD Type

The demand for video processing is rapidly increasing, driven by greater numbers of sensors with greater resolution, new types of sensors, new collection methods and an ever wider range of applications.
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