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PhD Studentship: Using Machine Learning to Understand the Role of the Soil Microbiome in Carbon Sequestration

University of Nottingham - Computer Science

Qualification Type: PhD
Location: Nottingham
Funding for: UK Students
Funding amount: See advert for details
Hours: Full Time
Placed On: 1st October 2024
Closes: 7th October 2024
Reference: SCI286

Supervisor: Hannah Cooper

Secondary Supervisor: Andy Neal (Rothamsted)

Subject Area:
 Soil Science, Computer Science

Research Title:
 Using machine learning to understand the role of the soil microbiome in carbon sequestration

Research Description:
Managing natural processes is one of the most practical and effective implementable approaches to removing CO2 from the atmosphere. It is imperative to measure carbon sequestered by natural means accurately, to understand process drivers and uncertainties and to accelerate nature-based carbon sequestration. Soil can store or sequester carbon through microbiological activity, providing a nature-based sink for CO2. However, poorly managed soils can release carbon as CO2 or methane (CH4) to the atmosphere - contributing to climate change and reducing soil health and fertility.
 
This project will develop machine learning (ML) platforms to monitor, quantify and reveal the processes underlying soil carbon sequestration. This approach combines measurements of physical, chemical, and biological functional and evolutionary processes. Soil microbiome research focuses on determining which microbial taxa and functions facilitate carbon capture across a range of climatic conditions. There will be an analytical challenge to integrate datasets of different types, scales and modalities. These relate to the processing and integration of soil chemistry, soil structure (tomographic imaging data) and metagenomic profiling of soil microbiome across different environmental conditions and soil textures. The overall aim is to integrate disparate measurements of physical, chemical, and biological processes in soil to develop a generalizable predictive model of carbon sequestration.

Keyword Search:
soil science, computer science, machine learning, artificial intelligence, soil carbon

Award Start Date: 01/12/2024

Duration of Award: 48 months

Terms and Conditions:
This research studentship is only available to UK citizens and includes payment of tuition fees and a tax-free stipend based on EPSRC rates

Applicant Qualification Requirements:

BSc degree in relevant science discipline

How to Apply:
email to hannah.cooper@nottingham.ac.uk

Closing Date: 07/10/2024

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