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University of Bath

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PhD in Mathematics and Artificial Intelligence for Hyperspectral Imaging University of Bath in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Funded PhD project, part-funded by Renishaw Plc, tenable for 4 years. Funding covers tuition fees, an enhanced stipend of £23,805 per annum for 2026/7, and access to a training support budget. Open to Home and International students, but international funding does not cover relocation to the UK, student visa costs, or the UK healthcare surcharge.

Deadline

Sep 13, 2026

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Country

United Kingdom

University

University of Bath

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Keywords

Computer Science
Data Science
Signal Processing
Information Technology
Mathematics
Artificial Intelligence
Computer Vision
Computational Mathematics
Hyperspectral Imaging
Statistics
ML

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About this position

The University of Bath is inviting applications for a funded PhD project in Mathematics and Artificial Intelligence for Hyperspectral Imaging, starting in January 2027. The project sits in the Department of Mathematical Sciences and is part-funded by Renishaw Plc.

This research will develop new, efficient, spatially-aware machine learning methods for hyperspectral imaging using modern mathematical optimisation techniques. The work combines computational mathematics, statistics, computer vision, data analysis, data science, and signal processing. Example topics include using spatial information to improve hyperspectral analysis, exploiting spectral correlations, reducing computational bottlenecks, and quantifying uncertainty for statistical decision-making.

The external sponsor, Renishaw Plc, will provide technical expertise on imaging modalities and real-world data. The successful candidate is expected to spend time based at Renishaw to generate data and receive training on their instruments and software.

Eligibility: applicants should have, or expect to obtain, a First Class or high Upper Second Class UK Honours degree (or equivalent) in a relevant subject. A master’s degree would be advantageous. A strong technical background and experience in mathematical methods are expected. Non-UK applicants must meet the programme’s English language requirement by the deadline.

Funding: the studentship is tenable for 4 years and covers tuition fees, an enhanced stipend of £23,805 per annum for 2026/7, and a training support budget. The studentship is open to both Home and International students, though international funding does not cover relocation to the UK, visa costs, or the UK healthcare surcharge.

How to apply: informal enquiries should be sent to Professor Matthew Nunes at [email protected]. Formal applications must be submitted via the University of Bath online application form for a PhD in Mathematical Sciences. Applicants should select EPSRC-DTG in the funding section and include the project title plus lead supervisor name. The advert may close early if a suitable candidate is found, so early application is recommended.

Funding details

Funded PhD project, part-funded by Renishaw Plc, tenable for 4 years. Funding covers tuition fees, an enhanced stipend of £23,805 per annum for 2026/7, and access to a training support budget. Open to Home and International students, but international funding does not cover relocation to the UK, student visa costs, or the UK healthcare surcharge.

What's required

Applicants should hold, or expect to receive, a First Class or high Upper Second Class UK Honours degree (or equivalent) in a relevant subject. A master’s level qualification would be advantageous. Applicants should have a strong technical background and experience in mathematical methods. Non-UK applicants must meet the programme’s English language requirement by the application deadline.

How to apply

Contact Professor Matthew Nunes for informal enquiries before applying. Submit the formal application through the University of Bath online application form for a PhD in Mathematical Sciences. In the funding section, select EPSRC-DTG, and in the project section quote the project title and lead supervisor name. Apply as early as possible because the advert may close early if a suitable candidate is found.

More information can be found here

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