Project Overview: This PhD project, based at the University of Southampton, investigates the impact of livestock grazing on carbon cycles and climate change by integrating satellite Earth observation, fieldwork, and artificial intelligence. The research aims to model ecosystem processes, scale findings from the UK to global levels, and assess the broader implications for agriculture and supply chains. Students will develop expertise in sustainability science and data-driven innovation, preparing for diverse careers in research, policy, and industry. Research Focus: Agriculture, especially livestock grazing, is a major contributor to global carbon emissions. This project addresses the urgent need to understand how grazing systems influence carbon storage and greenhouse gas fluxes. The student will combine satellite remote sensing, field measurements, and advanced machine learning to analyze the effects of livestock management on carbon dynamics. Fieldwork will be conducted at the North Wyke site of Rothamsted Research, providing hands-on experience with eddy covariance flux towers, GPS surveys, and land monitoring. On the computational side, the project leverages vision-language models to extract information from hyperspectral and high-resolution satellite imagery, linking ecosystem processes to agricultural practices. The student will learn process-based ecosystem modelling and data assimilation to enhance carbon cycle simulations, with the goal of scaling up results from local to national and global contexts. Integration of climate data with trade and supply chain information will enable a comprehensive assessment of livestock production's impact on sustainability and food security. Training and Environment: The IGNITE programme offers extensive personal and professional development, including hands-on training in eddy covariance flux measurements, GPS data collection, land surveys, data analysis, academic writing, and research dissemination. Advanced instruction in data assimilation, machine learning, deep learning, and Google Earth Engine applications is provided. The student will work within an interdisciplinary research group, collaborating with experts in AI, Earth observation, and agriculture at the University of Southampton, Rothamsted Research, and industry partners. Funding: The IGNITE Doctoral Landscape Award funds PhD researchers for 3.5 years (full- or part-time), providing a tax-free stipend at the UKRI standard rate (£20,780 for 2025/26), full Home tuition fees, an international fee waiver, and a Research Training Support Grant of £2,200 per year (£7,700 total). Eligibility: Applicants must have a UK bachelor’s degree with upper second-class honours or higher in a relevant subject, or an international equivalent. English language proficiency (IELTS 6.5 overall, minimum 6.0 in all components, or equivalent) is required. Both UK and international students are eligible, but only up to 30% of studentships can be awarded to international applicants. The programme encourages applications from diverse backgrounds and offers a guaranteed interview scheme for qualifying UK applicants from racially minoritised groups. Application Process: Applications must be submitted by 11:59pm on 8 January 2026 via the University of Southampton's online portal. Prospective students are encouraged to contact the lead supervisor to discuss suitability before applying. Applicants may apply for up to two projects but are advised to tailor their application to one. Both full-time and part-time study options are available. For further details, visit the project page or contact nerc-dla@soton.ac.uk .

Project Overview: This PhD project at the University of Southampton investigates how glaciers respond to climate change, with a particular focus on the role of subglacial hydrology in controlling glacier movement and subsequent sea level rise. As global temperatures increase, glacier melt accelerates, contributing to rising sea levels. However, the rate and nature of glacier retreat are strongly influenced by the presence and movement of water at the glacier bed, which affects the 'slipperiness' or effective pressure beneath the ice. Research Focus: The project aims to use advanced remote sensing techniques, specifically Sentinel-1 satellite imagery, to analyze glacier velocity and infer the nature of subglacial drainage systems across a range of glaciers worldwide. By applying offset tracking methods, the student will distinguish between distributed and channelized drainage systems, which have different implications for basal friction and glacier dynamics. The research will generate new insights into how subglacial hydrology modulates glacier speed, retreat, and their contribution to sea level rise, with findings relevant to both present and future climate scenarios. Training and Environment: The successful candidate will join the IGNITE Doctoral Landscape Award programme, benefiting from comprehensive personal and professional development opportunities. Training will cover glaciology, remote sensing, GIS, UAV survey, and photogrammetry. The student will use the European Space Agency's Sentinel Application Platform (SNAP) for data analysis and have access to high-specification workstations and the IRIDIS research computing facility at Southampton. The project is based in the School of Ocean and Earth Sciences, offering a vibrant, multidisciplinary research environment with strong academic, industrial, and policy networks. Funding: The IGNITE DLA provides 3.5 years of funding (full- or part-time), including a tax-free stipend at the UKRI standard rate (£20,780 for 2025/26), Home tuition fees, and a Research Training Support Grant of £2,200 per year. The University will waive the difference between Home and International tuition fees, making the opportunity accessible to both UK and international students. Additional support is available for conference attendance and training needs. Eligibility: Applicants should hold a UK bachelor’s degree with upper second-class honours or higher in a relevant subject (e.g., glaciology, geography, earth sciences, environmental science), or an international equivalent. English language proficiency is required (IELTS 6.5 overall, minimum 6.0 in all components, or equivalent). The programme encourages applications from diverse backgrounds and offers a guaranteed interview scheme for qualifying UK applicants from racially minoritised groups. Application Process: Applications must be submitted by 11:59pm on 8 January 2026. Prospective students are strongly advised to contact the lead supervisor to discuss the project and their suitability before applying. Applications should be tailored to this project, though a maximum of two projects may be applied for. Both UK and international students are eligible, but international studentships are limited and highly competitive. For further details, visit the University of Southampton website or contact the IGNITE DLA team.

This PhD project at the University of Southampton focuses on modelling the migration patterns of pollinating bats and their critical role in sustaining ecosystems and human societies. The research aims to understand how long-distance bat migrations are synchronized with flowering plants, a process influenced by environmental variables and habitat productivity. By integrating approaches from biodiversity, ecology, zoology, data science, machine learning, and remote sensing, the project seeks to reveal the mechanisms underpinning bat migration and the ecosystem services they provide. Supervised by Dr VZG Zamora-Gutierrez, Prof J Dash, Dr K Peh, and Prof J Travis, the student will join the School of Ocean and Earth Sciences, benefiting from interdisciplinary expertise and access to cutting-edge research facilities. The project is ideal for candidates interested in conservation biology, ecological modelling, and the application of advanced computational techniques to real-world environmental challenges. Applicants will have the opportunity to develop skills in data analysis, remote sensing, and machine learning, contributing to a deeper understanding of how environmental changes impact pollinator dynamics and ecosystem health. The research outcomes are expected to inform conservation strategies and policy decisions related to biodiversity and ecosystem management. The application deadline is 8 January 2026. Prospective students are encouraged to prepare a strong application highlighting their academic background and research interests relevant to the project. For more information and to apply, visit the official project page.