Identifying network mechanisms of neuronal population responses to in-vitro electrical stimulation: A computational modelling approach

Project summary Work towards a PhD degree, that will develop a computational network model of complex biological system. You will investigate how different types of node interconnectivity patterns affect simulated behavioural patterns of a biological system of interest at rest and under stimulation, e.g., the iPSCs-derived neuronal population dynamics. The aim of this project is to identify the network mechanisms underpinning the response of in-vitro neuronal population to electrical stimulation. The successful candidate will numerically solve three networks of neuronal models to infer the temporal-spatial and spatiotemporal modes of neuronal dynamics in the mesoscopic scale in the presence of electrical stimulation. We offer • A dynamic, stimulating and exciting research environment. You will be part of a unique innovative multidisciplinary research team focusing on mathematical and clinical neuroscience in a large Central Clinical School of Monash's leading University adjacent to Alfred Hospital • Ready access to research data such as spiking activity of iPSC-derived neurons, EEG and MRI with an opportunity for clinical data interpretation. 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 bridging the scales of the human brain and heterogeneous neuronal dynamics. You will have a background in one of the following areas: Applied mathematics, Electrical Engineering, Biomedical Engineering or 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. This includes evidence of one of the following: 1. A bachelor’s degree with honours class IIA or better from approved universities, which should include a relevant research component (for either MPhil or PhD position). 2. A research Master’s degree (for a PhD position). 3. A coursework Master’s degree and an overall GPA (grade point average) equivalent to 3.0 on the 4.0-point Monash scale, which should include a relevant research component (for a PhD position). 4. A postgraduate degree of at least one-year full-time equivalent with an overall GPA (grade point average) equivalent to 3.0 on the 4-point Monash scale, together with demonstrated research experience equivalent to honours IIA may be considered for PhD entry. 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, and 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 Scholarship support in the Graduate School’s competitive scholarship round (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 Monash scholarship, or a domestic equivalent scholarship, for stipend and tuition support https://www.monash.edu/graduate-research/future-students/apply. 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 Monash scholarship round. The duration of the candidacy is 3 years with 2 possible extensions each for up to 6 months. Inquiries & 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 (steve.mehrknaoon@monash.edu).