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ONE Planet DTP - Using machine learning based approaches to predict changes in microbial signatures that describe anthropogenic environmental change (Ref: OP20278)

  • Full or part time
  • Application Deadline
    Friday, January 31, 2020
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

The impact that the construction of new dwellings has on our rural and urban environments is still in its infancy. Understanding this is of the utmost importance as the UK government has pledged to build half a million homes between 2020 and 2022 with more expected thereafter to meet the demand of a growing population. We are becoming increasingly aware that the structure of bacterial communities can act as a marker of environmental change due to their response to changing conditions. An example of this could be the role of microorganisms in the generation of greenhouse gases, or their positive roles in fixing carbon. Current bioinformatics tools allow microbial genomic data to be analysed and when supplemented with modelling approaches can identify key differences in the microbiome associated with environmental change. Computational methods offering the ability to predict changes in microbial communities however are less well understood. These approaches may predict key microbial signatures that allow the ability to intervene and prevent wider ecological impact.
The key aim of this study therefore is to build on published methods and develop more relevant machine learning approaches, using microbiome data, to predict how new housing developments will influence their environment and how these build into future global challenges. We will supplement this study by focussing locally on the impact of construction on environmental change, by following a time course of sampling to predict changes in the microbiome over time. Supplementing the microbiome data with other environmental parameters such as local topography and weather conditions will allow us to identify dispersal effects and therefore the wider impact on both microbial and environmental change. This work will allow us to determine and predict the ecological scar that building a dwelling has on a specific environment. Importantly these models could be trained to any environmental microbiome dataset as a predictive tool for environmental change and therefore the final part of this study will illustrate this ability to translate these methods to other environments using published and collaborative data to further illustrate their impact
This project will offer relevant skills for microbial/environmental ecologists utilising wet lab based molecular biology skills with access to the latest genomic technologies at Northumbria University including Illumina MiSeq and NextSeq, Pacific Biosciences Sequel and Oxford Nanopore GridIon. Furthermore, the university has invested in high performance computing which can be used to build and test the bioinformatics and machine learning that builds into the ecology of the environments investigated. This project builds into the Research England funded Biotechnology in the Built Environment project looking at the ecological impact of architecture, engineering and design of our dwellings on environmental change and this study will have access to supporting resource from this funding scheme.
Prerequisites:
BSc Hons 2:I or above in biology, microbiology, bioinformatics or machine learning. An MSc in a related area would be preferred.
For more information, please contact Dr Darren Smith ().

Eligibility and How to Apply:
Please note eligibility requirement:
• Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
• Appropriate IELTS score, if required.
• Applicants cannot apply for this funding if currently engaged in Doctoral study at Northumbria or elsewhere.

Please note: Applications that do not include a research proposal of approximately 1,000 words (not a copy of the advert), or that do not include the advert reference (e.g. OP.....) will not be considered.

Northumbria University takes pride in, and values, the quality and diversity of our staff. We welcome applications from all members of the community. The University holds an Athena SWAN Bronze award in recognition of our commitment to improving employment practices for the advancement of gender equality.

Funding Notes

We have a minimum of 12 (3.5 year) PhD fully funded studentship awards available for October 2020 entry. Each award includes fees (Home / EU), an annual living allowance (for 2019/20 this is £15,009) and a Research Training Support Grant (for travel, consumables, as required).

References

Cavicchioli, R., Ripple, W.J., Timmis, K.N. et al. Scientists’ warning to humanity: microorganisms and climate change (2019). Nat Rev Microbiol 17, 569–586
Singh, B., Bardgett, R., Smith, P. et al. (2010). Microorganisms and climate change: terrestrial feedbacks and mitigation options. Nat Rev Microbiol 8, 779–790

Delgado-Baquerizo, M., Maestre, F., Reich, P. et al. (2016). Microbial diversity drives multifunctionality in terrestrial ecosystems. Nat Commun 7, 10541

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