Applications are invited for a PhD studentship (nominally 3.5 years) to join the Quantum Systems and Devices group and the Clinical Imaging Sciences Centre (CISC) at the University of Sussex to develop brain imaging techniques. This is a multidisciplinary project which combines cutting edge research techniques in quantum physics, biomedical engineering and medical imaging. We are investigating ways to use quantum sensors to yield uniquely rich information on the spatial, spectral and temporal magnetic signatures of human brain function. In a significant advance from current brain imaging technology (magnetoencephalography - MEG), we are able to bring sensors to within a few millimetres of the scalp (in contrast to several centimetres in conventional MEG systems). This promises increased sensitivity compared to traditional imaging systems, enabling new insight into the brain and behaviour.

We intend to combine measures from such quantum sensors with advanced MRI techniques developed at CISC to study the relationship between tissue microstructure and neurophysiology in the human brain and the spinal cord. This approach will exploit the high temporal resolution of MEG and the great anatomical detail and sensitivity to microstructure provided by MRI.

This novel strategy to characterise the functional anatomy of the central nervous system will allow us to investigate the mechanisms of brain plasticity in healthy and diseased brain, and will be of great potential in understanding pathologic changes occurring in diseases such as multiple sclerosis and motor neuron disease. It will help to address questions such as "Is there a direct link between tissue microstructure and measurement made at behavioural level?" or "Can we exploit neuroplasticity to compensate the impairment caused by neurological conditions?"

The student will experience research training within an inter-disciplinary team of physicists, neuroscientists and experts in medical computing and neuroimaging, providing core skills through which to pursue a career at the interface between physics and neuroscience.

The successful applicant will have some technical background in one of the sciences and be proficient in computer programming. Some knowledge of medical imaging is an advantage, as is some background in neuroscience