PhD Studentship: Electrical Sensing of Dynamic Cardiovascular Volume in a Benchtop Model

Overview

The University of East Anglia is offering a research project titled Electrical Sensing of Dynamic Cardiovascular Volume in a Benchtop Model, supervised by Dr Dennis Fitzpatrick. It is a Masters by Research programme and is offered on a self-funded basis, open to applicants who are self-funded or are in the process of securing external funding.

Cardiovascular disease is a major global health challenge that drives innovation in medical technology, and there is strong demand for ways to obtain physiological information accurately, continuously and with low-power sensing. Cardiac chamber volume underpins measures such as stroke volume and ejection fraction and helps in assessing heart failure and valvular heart disease. Today it is mostly assessed with imaging such as echocardiography and cardiovascular magnetic resonance, which tend to give measurements at particular moments rather than a continuous signal.

The project asks whether low-energy electrical measurements can provide a reliable estimate of changing fluid volume within a cardiovascular system. It starts with building a simple benchtop phantom in which fluid volume can be changed in a controlled and independently measurable way. Purpose-designed electrodes apply and detect low-energy electrical signals, and the results are compared with known volume changes. The student explores how different configurations affect the relationship, and later stages may add more complex geometries, time-varying volume changes and more physiologically realistic models. MATLAB, Python or similar tools are used for signal processing and quantitative comparison. Both positive and negative findings are valued, since they define the limits of the approach. The work is entirely laboratory based and does not initially involve patients, animal experiments or implanted devices.

Who can apply

Applicants need at least a 2:1 bachelor's degree or equivalent in electrical or electronic engineering, biomedical engineering, bioengineering, physics or applied physics, mechatronics, computer science or data science, applied mathematics or a closely related quantitative discipline. People from other backgrounds are considered if they can show relevant experience in electronics, instrumentation, programming or signal processing.

Key dates

The closing date is 23 November 2026, and the start date is 1 February 2027.