Dear all,

We would like to advertise 1x Postdoc and 1x PhD position in Systems Neuroscience and Complexity at The University of Sydney.

The successful candidates will join a dynamic interdisciplinary collaboration between A/Prof Mac Shine (Brain and Mind Centre), A/Prof Joseph Lizier (School of Computer Science) and Dr Ben Fulcher (School of Physics), within the University's Centre for Complex Systems, focused on advancing our understanding of brain function and cognition using cutting-edge computational and neuroimaging techniques at the intersection of network neuroscience, dynamical systems and information theory.
The positions are funded by a grant from the Australian Research Council "Evaluating the Network Neuroscience of Human Cognition to Improve AI".

Post-Doctoral Fellow in Systems Neuroscience and Complexity: Full time, research only fixed term position for 24 months.
Lead supervisor: A/Prof. Mac Shine
The Postdoc will process and analyse functional neuroimaging data (fMRI, EEG, etc.) to extract meaningful insights into brain function. The successful candidate will hold a PhD in Neuroscience, Computational Neuroscience, Psychology, or a related field (by July 2024); have a strong background in computational modelling and/or functional neuroimaging techniques; and proficiency in programming languages commonly used in neuroscience research (e.g., Python, MATLAB).

PhD scholarship: Characterising information flow networks across brain regions in rest and task: available to both domestic and international applicants for 3.5 years (fulltime), providing the tuition fees and a stipend.
Lead Supervisor: A/Prof. Joseph Lizier
The PhD student will conduct applications of, and/or updates to algorithms for, inferring brain network models to represent information flow relationships between brain regions (via information-theoretic measures), based on time-series neural recordings. The successful candidate will hold a Bachelor's degree with honours or Master's degree in a relevant quantitative field (e.g. computer science, physics, mathematics), including completing a research thesis (first-class honours equivalent results are essential); and excellent skills in computational numerical analysis (in Python and/or Matlab) and in applied mathematics.