About the Project
Using these techniques the student will use actively and passively collected data from different atmospheric and meteorological sources to develop ways of extracting biological information. These methods will then be used to analyse real-world data sets to investigate and visualise spatio-temporal patterns in the biological data to test old hypotheses with this new approach. We will target hypotheses that have been simply intractable to contemporary methods of biological study due to the scale of data that has been required. The student will be able to explore not only spatio-temporal analysis, geostatistics, and macroecology, but also data visualisation and communication of outputs to stakeholders.
This PhD project has an exciting interdisciplinary focus that will produce considerable impact. Key external partners both within the UK (Natural England, Centre for Ecology and Hydrology, BugLife) and abroad (in the US and South Africa) who will be involved in discussion and guiding the project. The project would benefit from a student with strong quantitative skills in data analysis (including training specifically in data science, if possible), an interest in harnessing the power of large datasets for novel purposes, and an interest in solving real world environmental problems.
Candidates should have, or be expecting, a 2.1 or above at undergraduate level in a relevant field. If English is not your first language, you will also be required to meet our language entry requirements. The PhD is to start in Oct 2018.
Please apply online here: https://studentservices.leeds.ac.uk/pls/banprod/bwskalog_uol.P_DispLoginNon When you apply, please include the project title and supervisor name, and upload a CV and transcripts.
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