The Biomarkers for Environmental and Climate Science (BECS) research group at the University of Glasgow is looking to recruit an excellent PhD student to apply advanced statistical and computing techniques to large environmental datasets with an aim to identify ecosystem responses to abrupt and extreme environmental change.
Climate and environmental change pose one of the biggest risks to society and ecosystems worldwide. As humans begin to modify their behaviour and practices around greenhouse gas emissions and renewable energy, Earth’s natural system responds to the long- term effects of the continued stresses. What is not known yet is how much is too much? Understanding how ecosystems have responded to similar, abrupt stresses in the past is the key to understanding how they are responding now and how resilient they will be to future changes.
In this project, the PhD student will join a collaborative team of transdisciplinary scientists who combine geochemistry, ecology, advanced statistics and computing to elucidate complex environmental relationships in lake ecosystems perturbed by extreme events. In particular the application of AI to these complex challenges is novel, so the project will ground truth autonomous learning with scientific expertise in environmental change and stressors. The BECS research group at the University of Glasgow (UoG) uses organic biomarkers as tracers of single environmental stressors (e.g., temperature, salinity), to identify extreme environmental events. Establishing and validating biomarkers requires in-depth knowledge of the organisms that produce them, as well as the complex interactions with the environments in which they live.
In this project, the student will work closely with co- supervisor Dr. Claire Miller (UoG) to interrogate the large temporal and spatial environmental datasets held at the UoG and the Centre for Ecology & Hydrology (CEH) with a goal to create fast automatic detection of extreme environmental stressors that can be implemented into early warning systems. The ultimate outcome would be for this to result in extremely cost-effective prediction of abrupt events.
Specifically, the PhD student will have access to biomarker development data from regional projects within the BECS group, and environmental relationships determined from generalised linear model approaches (i.e., Plancq et al. 2018). The PhD student will test these relationships using the same dataset, but more advanced techniques for examining interactions between stressors (e.g. Generalised Linear Mixed Effects Models Boosted regression trees and random forests). The techniques developed in the first stage of the project will be applied in collaboration with co-supervisor, Prof. Carvalho’s Freshwater Restoration and Sustainability Group, at
CEH Edinburgh, to a broader phytoplankton dataset from >700 European lakes. CEH also has strong links with national and international stakeholders and will work with the successful applicant to consult these at an early stage to co-develop ways to use the results from the project in a way that is useful to these stakeholders.
The aim of the project is to use advanced data techniques on big environmental datasets to identify information gaps, environmental stressors, and solve persistent challenges in reconstructing past extreme climate events. Combining the freshwater ecology expertise of CEH, with the focus of understanding and applying past climate and environmental change in BECS, and with AI approaches to spatio-temporal interrogation of big data in the Maths and Stats Dept will enable novel insights to environmental processes (i.e., droughts and floods, lake eutrophication, harmful algal blooms) that will assist in managing current and future environmental stressors.
For more specific details on this project, including training and placement opportunities, please see the full advertisement at: http://www.iapetus.ac.uk/wp-content/uploads/2018/10/IAP2-18-56_Glasgow_Toney1.pdf
or contact Professor Jaime L. Toney at the University of Glasgow
Eligibility & Requirements: All applicants need to meet NERC’s eligibility criteria to be considered for an IAPETUS studentship and these are detailed in NERC’s current studentship handbook.
IAPETUS is only able to consider applications from Home/European Union candidates. International candidates are not eligible to be considered and where an candidate from another EU country has not been resident in the UK for 3 years or more prior to the commencement of their studies with IAPETUS, they will only be eligible for a fees-only studentship.
IAPETUS is looking for candidates with the following qualities and backgrounds:
- A first or 2:1 undergraduate degree, or have relevant comparable experience;
- In addition, candidates may also hold or be completing a Masters degree in their area of proposed study or a related discipline; &
- An outstanding academic pedigree and research potential, such as evidenced through the publication of articles, participation in academic conferences and other similar activities.