Research Associate in Eis Data Analysis for Oral

2 weeks ago


Sheffield, Sheffield, United Kingdom University of Sheffield Full time

The Department of Automatic Control and Systems Engineering at University of Sheffield is recruiting a Research Associate in Electrical Impedance Spectroscopy Data Analysis for Oral Cancer Diagnosis.


Electrical Impedance Spectroscopy (EIS) - a technique where a small alternating current is passed through a tissue and the resulting impedance measured over a range of frequencies - has previously been applied for detecting cervical pre-cancers.

The project aims to adapt the EIS for use in oral tissues, specifically to identify potentially malignant precancerous lesions in the mouth.

Machine leaning approaches will be developed, which will be applied to process the EIS data from oral tissues and associated medical information for oral cancer diagnosis.

In this project, in order to facilitate the machine learning model building, the virtual oral tissue models will be developed based on knowledge derived from tissue-engineered constructs developed within the School of Clinical Dentistry.

Simulated data produced in the Department of Computer Science will augment the EIS data collected from these constructs.

The machine learning models will then be developed from both the simulated EIS data and that collected from tissue-engineered constructs.

Finally, a prototype decision support system dedicated to the EIS based oral cancer diagnosis will be produced based on the machine learning models for possible future clinical use.


This is an exciting opportunity for a motivated researcher educated to PhD level (or close to completion, or with equivalent experience) to contribute to the development of the EIS based machine learning models and associated implementation system to improve early oral cancer diagnosis.

This is cross-disciplinary research project and will involve investigators from across the University of Sheffield (Department of Computer Science, ACSE, and Clinical Dentistry) and beyond.

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