University of Southampton
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PhD in Machine Learning for Large-Scale Distributed Acoustic Sensing Across Environments University of Southampton in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Competition funded PhD project. Funding details are not specified in the post, but the project is presented as a funded doctoral opportunity.
Deadline
Jul 1, 2027
Country
United Kingdom
University
University of Southampton
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About this position
PhD opportunity at the University of Southampton in machine learning for large-scale distributed acoustic sensing (DAS) across urban, coastal, and maritime environments.
This project focuses on developing computational methods for analysing large, noisy, and difficult-to-label DAS datasets. You will work on machine learning, signal processing, and spatiotemporal data analysis to detect, classify, localise, and separate events in fibre-optic sensing data. Possible research directions include self-supervised or weakly supervised learning, representation learning, uncertainty and interpretability, domain adaptation, efficient high-volume processing, and validation with incomplete ground truth.
The research has applications in infrastructure monitoring, transport, environmental monitoring, marine sensing, ocean acoustics, ecological monitoring, and hazard detection. The project builds on the SOUNDSCALE project and uses datasets from the south of England, London, and maritime settings, with opportunities to combine DAS measurements with vehicle counts, air-pollution records, and local-authority data.
You will be based in the School of Electronics and Computer Science within the Faculty of Engineering and Physical Sciences, with access to high-performance computing (Iridis), training through the ECS Graduate School and Doctoral College, and potential collaboration with the National Oceanography Centre. Additional opportunities may include teaching, conference participation, engagement with the Alan Turing Institute and Responsible AI UK, and support for commercialisation through Future Worlds.
Funding: competition funded. Degree: Doctor of Philosophy (PhD). Entry requirement: 2:1 UK honours degree or equivalent. Deadline: 1 July 2027.
Funding details
Competition funded PhD project. Funding details are not specified in the post, but the project is presented as a funded doctoral opportunity.
What's required
Applicants should have a 2:1 UK honours degree or equivalent. The project is suited to candidates interested in machine learning, signal processing, spatiotemporal data analysis, data fusion, uncertainty and interpretability, and high-volume computational methods. Experience or interest in environmental, marine, transport, or infrastructure sensing would be beneficial.
How to apply
Review the project page and the full entry requirements, then use the university's PhD application process linked from the project page. Prepare your academic transcripts and supporting documents before the closing date.
More information can be found here
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