Research Associate: Neurodevelopment and Mental Health

Department : Perinatal Imaging & Health

The successful candidate will play a key role in analysing data from a longitudinal cohort of children who were born very preterm. Working closely with Lead Investigators, the successful candidate will contribute to the timely completion of the research programme. We are seeking to appoint a neuroimaging data scientist/engineer to develop and apply state of the art machine learning methods to analyse multimodal longitudinal imaging data collected from birth to mid-childhood, in order to identify the brain-behavioural characteristics of children who are at risk of developing mental health disorders. The successful candidate will play a key role in analysing longitudinally collected brain imaging data. He/she will work on integrating cognitive, behavioural and psycho-social outcomes data and a range of imaging modalities to detect, characterise, and ultimately predict the emergence of mental health problems. These data will be used to develop predictive models of child outcome in relation to early detection, disease status, and prognosis. The study is supported by the Medical Research Council and aims to investigate the biological mechanisms associated with the risk of developing psychopathology in premature children. A second research goal is to explore whether information about brain development and peripheral inflammation acquired around the time of birth could be used to identify early in life those premature children who are at greater risk of developing psychopathology.
This post will be offered on a fixed-term contract 2 years.
This is a full-time.
The selection process will include a panel interview and a presentation.

Full info here.

ML imaging position @ King’s College London