Fully-funded PhD studentship in Biomedical/Neural Engineering at Trinity College Dublin

Applications are invited for a highly motivated PhD student to join an exciting new project that will use high density electromyography (EMG) and electroencephalography (EEG) to examine changes in neuroelectric signalling in Amyotrophic Lateral Sclerosis (ALS). This is a 4-year funded PhD studentship.

ALS, also known as motor neuron disease, is a nervous system disease that causes a progressive loss of muscle control. One of the major challenges in the diagnosis and assessment of ALS is the lack of biomarkers to quantify changes in motor function. Recently, research from the Academic Unit of Neurology (AUoN) in Trinity College Dublin has shown that information from signals recorded from the brain (EEG) and muscle (EMG) can identify distinct differences in sensorimotor network function in motor neuron diseases (doi: 10.1093/brain/awab322; doi: 10.1093/cercor/bhad152). This project will examine whether features of high density surface EMG signals can be used to detect early signs of motor unit dysfunction.

In this role the successful candidate will use dimension reduction techniques and nonlinear dynamic measures to examine the high density EMG structure (with a particular focus on entropy measures). The aim of the project is to assess whether features of the high density EMG signals can sensitively detect subtle signs of motor unit degeneration in people with ALS. To address this aim, the high density EMG analysis will first be refined and tested using simulated data and data from healthy participants, before being applied to signals recorded in people with ALS. This project will be in collaboration with Dr Matthew Flood, the developer of EntropyHub in Julia (JuliaHub).

Full details of this position and how to apply can be found here.