Brain development in infants and its disruption by preterm birth or perinatal injury, can be measured with functional MRI (fMRI). Unfortunately, infants move in the scanner and half the images are discarded, precluding clinical application. In recent years, deep neural networks (DNNs) have led to breakthroughs in artificial intelligence and are finding growing application in biomedical imaging. DNNs have considerable potential to correct head motion in fMRI, as they can learn complex mappings, and exploit knowledge of brain structure. The PhD Candidates will develop DNNs to motion correct fMRI data.
Candidates must have expertise in at least one of the two following areas and must be willing to develop skills in the other:

*  design and optimisation of deep neural networks
*  neuroimaging
Candidates must have expertise in programming in python or another language.

The studentships comprise EU fees, stipend and conference travel.

Further details: LINK, PDF

Deadline 12 noon on April 22, 2024.