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University of Southampton
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Fully Funded PhD in AI for Signal Processing of Exposome LC-HRMS Data University of Southampton in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Fully funded for UK applicants only. The advert does not specify the stipend amount or detailed tuition-fee coverage.
Deadline
Jan 10, 2027
Country
United Kingdom
University
University of Southampton
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About this position
This PhD project develops artificial intelligence methods for signal processing in non-target liquid chromatography and gas chromatography high-resolution mass spectrometry (LC/GC-HRMS) data. The research addresses major challenges in computational mass spectrometry, including severe background noise, overlapping peaks, complex feature alignment and structural deconvolution in high-dimensional datasets.
The project will create advanced transformer-based workflows tailored to multidimensional scientific data. By exploiting patterns across retention time, mass-to-charge ratios and signal intensities, the research aims to establish next-generation architectures for automated mass-spectrometry analysis.
Using self-supervised and generative deep-learning models trained on large spectral datasets, the PhD researcher will develop workflows for robust noise suppression, precise peak picking and accurate fragment deconvolution. These tools will be designed, validated and applied to large-scale biological samples.
The work connects deep learning, computational mass spectrometry and environmental health sciences. Its applications relate to the human exposome—the collection of environmental chemical exposures experienced across a lifetime—and to improving chemical discovery and the accuracy of environmental health analysis. The project is based within the School of Chemistry and Chemical Engineering at the University of Southampton, with an interdisciplinary research environment focused on AI for science and real-world environmental health challenges.
Funding details
Fully funded for UK applicants only. The advert does not specify the stipend amount or detailed tuition-fee coverage.
What's required
Applicants require a 2:1 honours degree. The project is interdisciplinary and would suit candidates interested in artificial intelligence, deep learning, transformer models, computational mass spectrometry, environmental health, chemical discovery and analysis of biological samples; the full entry requirements should be checked on the University of Southampton project page.
How to apply
Review the full project and entry requirements on the University of Southampton webpage, then submit an application through the university's postgraduate research application process for this project before 10 January 2027.
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Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.