Decoding gastric electrical activity non-invasively

Dr Recep Avci

• Applications accepted all year round
• Funded PhD Project (Students Worldwide)

About the Project

This project offers an exciting opportunity to contribute to the development of new computational tools for the personalised, non-invasive assessment of stomach function. Gastric motility disorders such as gastroparesis and functional dyspepsia are associated with abnormal patterns of electrical activity in the stomach, but identifying these abnormalities non-invasively remains a major challenge. By combining experimental data, subject-specific anatomical modelling, and advanced computational methods, this project aims to help bridge that gap and support the development of future diagnostic tools.

The student will work on a highly interdisciplinary project at the interface of biomedical engineering, physiology, computational modelling, and medical signal analysis. The research will involve developing subject-specific models to understand how stomach activity is reflected in non-invasive body-surface recordings, and using these models in characterisation of electrical activity in the stomach. The project will draw on unique experimental datasets and anatomically detailed models, providing an excellent opportunity to gain experience in both fundamental and translational research.

This is a great project for a motivated student who is interested in applying mathematics, computation, and engineering to solve clinically relevant problems. The successful candidate will contribute to innovative research with strong potential for real-world impact, while building skills in modelling, data analysis, and biomedical research that can lead naturally to further postgraduate study, including a PhD.

Desired skills

A background in biomedical engineering, electrical engineering, physics, mathematics, computer science, or a related field is preferred. The ideal candidate will have an interest in computational modelling, biomedical signal analysis, and medical applications of engineering. Experience with programming (preferably MATLAB or Python), data analysis, and numerical methods would be advantageous. Strong quantitative and problem-solving skills, along with the ability to work both independently and in an interdisciplinary team, are also desirable.

Funding Notes

Marsden Fast Start funding