Neonatal brain network dynamics in the preterm period: A mathematical-clinical neuroscience approach

Little is known about how the neuronal circuits and neuronal population dynamics in the brain of preterm-born infants can be adequately characterised in from Early (30-32 weeks gestation) to Term-equivalent age (40-42 weeks gestation). This PhD project aims at identifying neonatal brain network systems. Work towards a PhD degree, that will identify the neuronal mechanisms underpinning neurotypical brain function development in newborn infants. You will integrate biologically plausible network models and neonatal electroencephalography (EEG) to investigate the role of network architectures obtained from neuroimaging data, neuronal synchronisation and de-synchronisation patterns in the emergence of normal and abnormal brain function in infants born preterm. A multimodal neuroimaging approach and combination of state-of-the-art methods (MRI-imaging, EEG, dynamical systems theory, connectomics and network science) will be used to uncover the global functional brain network organisation in infants as well as specific local neuronal dynamics that drive heterogenous EEG patterns in the preterm period. We offer • A dynamic, stimulating and exciting research environment. You will be part of a unique innovative multidisciplinary research team focusing on perinatal neuroscience and neurodevelopment in a large leading clinical and translational research environment adjacent to Monash Children’s Hospital. • Ready access to clinical EEG and MRI data with an opportunity for hands on clinical data acquisition from infants. The Person - profile and requirements You will be highly motivated to apply your theoretical and experimental skills to make a real difference in the exciting emerging area of newborn brain development and neuro-rehabilitation. You will have a background in one of the following areas: Applied mathematics, Electrical Engineering, or theoretical and computational Physics.You will need to meet the requirements of admission to a Research Higher Degree at Monash University, as described at https://www.monash.edu/study/why-choose-monash/courses-explained/research-degrees. You will also need to be 1. self-motivated and ready to put enthusiasm in the project, 2. an experienced programmer in one of the following languages: MATLAB/Python, 3. a good team player. Scholarships and Remuneration If you are our successful applicant, we will invite you to apply for PhD admission. As part of the application process you can request to be nominated for Monash Graduate Scholarship (MGC) (https://www.monash.edu/study/fees-scholarships/scholarships/find-a-scholarship/monash-graduate-scholarship-mgs), if required. The award of a PhD scholarship is not guaranteed. The applicants need to demonstrate an evidence of publication. Prospective students will be provided with assistance to apply for a competitive MGC, or a domestic equivalent scholarship, for stipend and tuition support. Award of a scholarship will be conditional upon the applicant applying for and obtaining an unconditional offer for entry to the PhD program at Monash and being assessed in the next available MGC round. Enquiries and Application If you want to join our research team in this role, please send an email outlining your motivation, along with your CV with contact details of two referees to Dr Steve Mehrkanoon via steve.mehrkanoon@monash.edu Principal Supervisor: Dr Steve Mehrkanoon https://www.monash.edu/medicine/scs/researchers/steve-mehrkanoon https://research.monash.edu/en/persons/steve-mehrkanoon Co-supervisor: Professor Rod Hunt https://www.monash.edu/medicine/scs/researchers/rod-hunt https://research.monash.edu/en/persons/rod-hunt Scholarship is available for Winter/Summer Project applicants from Monash University.