Call for post-doctoral Research Fellow
Dublin City University
Call for post-doctoral Research Fellow. We are inviting applications for a 24-month Post-doctoral Research Fellow position as part of the NeuroInsight Marie Skłodowska-Curie COFUND Action for Postdoctoral Fellowships.
NeuroInsight is a collaboration between the FutureNeuro SFI Research Centre for Chronic and Rare Neurological Diseases and the Insight SFI Research Centre for Data Analytics.
Neurodegenerative disorders, such as Alzheimer’s disease, Multiple Sclerosis, and Parkinson’s disease are devastating and incurable conditions that affect the central nervous system and are caused by the progressive degeneration of neurons. Early detection of these disorders is critical for treatment and improved prognosis. Unfortunately, however, the most common detection methods in use today are expensive and often involve invasive tests in hospitals.
Although neurodegenerative disorders differ in their clinical manifestations and physiological bases, many, including Alzheimer’s disease, Multiple Sclerosis, and Parkinson’s disease, present with a common characteristic: distinctive eye fixation patterns. Recent research has demonstrated that eye fixation patterns, such as fixations, saccades, and the interaction between eye movements and tasks, can provide insights into neurological function and processes, and could have potentially important clinical applications.
The goal of this project will be to investigate the use of eye tracking technology in combination with analysis techniques from machine learning and deep learning to develop new technologies for computer-aided early diagnosis and monitoring of neurodegenerative disorders. To this end, the project will identify a cohort of subjects presenting with neurodegenerative disorders in various stages along with a cohort that do not present symptoms of disorder and attempt to use data from eye tracking devices to classify the presence and severity of the disease, as well as identify common characteristics across subjects that may have clinical significance. Beyond accuracy, emphasis will also be placed on developing techniques that are interpretable and which may provide insights into the underlying condition.
Existing high-performance eye tracking technologies are often too expensive to be feasibly used outside of a clinical setting in many circumstances. High-resolution consumer video camera technology is, on the other hand, inexpensive and readily available in a wide range of consumer electronics devices such as laptops and smartphones. A second goal of this project will be to establish if state-of-the-art computer vision techniques applied to data from consumer cameras allow sufficiently high-fidelity eye tracking for diagnostic or screening purposes. The development of such a technology could represent a significant breakthrough that would allow for testing and monitoring neurological disorders in the home.