About the Position
The University of Bath is inviting applications for the following project, part-funded by Renishaw Plc, starting in January 2027.Overview of the Research:Advances in hyperspectral imaging have resulted in high-quality images at fine spatial resolutions over hundreds of spectral wavelengths. Being able to efficiently make use of this information has the potential to provide scientific and industrial insight in several application areas, from medical diagnosis to geophysical mineral exploration. This project will develop new, efficient, spatially-aware machine learning methods for hyperspectral imaging based on modern mathematical optimisation techniques.Example research questions we aim to address in this project are:How can we harness spatial information to improve hyperspectral analysis?How can we take advantage of spectral correlations?What are the computational bottlenecks and how do we circumvent them?Can we quantify uncertainty to support statistical decision-making?The mathematical methods developed in this project will involve aspects of statistics, optimisation and signal processing.The external sponsor for the project will be Renishaw Plc, providing technical expertise on imaging modalities, in particular hyperspectral imagery for clinical (as well as other) applications, including working knowledge of current state-of-the-art data processing techniques and requirements. The joint research and collaboration ensures that the mathematical and AI methods developed are grounded in practical feasibility and tested on real-world data.It is expected that the successful candidate will spend time based at Renishaw in order to generate real life data to be used in the study and will be fully trained in the use of their instruments and software.Candidate Requirements:Applicants should hold, or expect to receive, a First Class or high Upper Second Class UK Honours degree (or the equivalent) in a relevant subject. A master’s level qualification would also be advantageous. Since the project will involve a significant methodological component, applicants will be expected to demonstrate a strong technical background and experience in mathematical methods in their application.Non-UK applicants must meet the programme’s English language requirement by the application deadline.Enquiries and Applications:Informal enquiries are encouraged and should be directed to Professor Matthew Nunes, [email protected] applications should be submitted via
Research Interests
- Develop new machine learning methods for hyperspectral imaging based on mathematical optimisation techniques.
- Conduct research on spatial information utilization and spectral correlations in hyperspectral data.
- Quantify uncertainty to support statistical decision-making.
Required Skills & Qualifications
- Mathematical Methods
- Statistics
- Signal Processing
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