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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

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Country

United Kingdom

University

University of Southampton

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Keywords

Computer Science
Chemistry
Environmental Science
Signal Processing
Deep Learning
Artificial Intelligence
Environmental Health

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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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