We are seeking a highly motivated data scientist to help us develop new technology to monitor debilitating neurological conditions. Nerve and muscle diseases, such as motor neurone disease, cause progressive paralysis. Many of these conditions have no cure and new research is held back by the lack of a means to determine disease progression.
Electrical impedance spectroscopy (EIS) is a simple, non-invasive way of assessing muscle health in which an imperceptible electrical current is passed through the muscle. We have developed a novel approach to EIS which assesses muscle architecture in greater detail than previously possible.
The aim of this project is to identify disease and track change over time by applying advanced signal processing techniques to real patient data. Through this work you will develop a new way for clinicians to diagnose and monitor patients with nerve and muscle diseases.
This exciting PhD is a collaboration between scientists at the Sheffield Institute for Translational Neuroscience (SITraN) and the Department of Automatic Control and Systems Engineering. You will work closely with clinicians and engineers and gain experience of multi-disciplinary team science.
The project will require candidates to have excellent mathematical and/or computational skills. Prospective candidates should have a good honours degree (Class 1 or 2:1) in Control, Electrical or Mechanical Engineering, Computer Science, Mathematics, Physics or other related disciplines.
A fully funded studentship provided by the Engineering and Physical Science Research Council (EPSRC) is available. The start date can be either March or October 2019.
The funding lasts for 3.5 years and includes Home/EU fees, as well as tax-free stipend at the UK Research Council rate (£14,777 for 2018/19). UK nationals and non-UK EU students who have been resident in the UK for 3 years prior to the start of the studentship are eligible to apply.
Employer: University of Sheffield
Location: Sheffield, England
Degree required: BS
Job posted: November 30th, 2018
Applications close: January 31st, 2019