"Postdoctoral Research Associate (Physics)"

Full time, 2-year fixed term position with potential to extend. Located on the Camperdown Campus at the School of Physics.

Exciting opportunity to conduct research in a world-leading interdisciplinary environment for studying the dynamics of complex physical systems.

Base Salary, Academic Level A, $113,634 - $113,634 p.a + 17% superannuation.

About the opportunity

The School of Physics at the University of Sydney is currently seeking a Postdoctoral Research Associate (Physics) to work within the Dynamics and Neural Systems Group, led by A/Prof Ben Fulcher, on developing novel methods to analyze non-stationary complex physical systems with applications to quantifying dynamical patterns in multivariate electrophysiological data of sleep dynamics. There is some freedom to tailor the specific research to the candidate, according to their expertise and interests, from more theoretical projects focused on characterizing non-stationary complex systems, through to more data-driven applications of such methods. The associated research is supported by an ARC Future Fellowship.

Your key responsibilities will be to:

• interact positively and productively with members of the Dynamics and Neural Systems Group
• develop new understanding of non-stationary complex systems through theoretical analysis and numerical simulation
• develop efficient statistical algorithms for analyzing and inferring dynamical models from multivariate time-series data
• assist in the supervision of PhD and Honours students working on related topics, including the analysis of large-scale sleep recordings from a dynamical systems perspective.

About you

The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity. As such, we see the importance of recruiting talent aligned to these values and are looking for a Postdoctoral Research Associate who has:

• a PhD in a quantitative field (e.g., physics, mathematics, computer science)
• interest and experience in simulating and analyzing multivariate time-series data
• interest and experience developing and working with open scientific software
• interest in analyzing the dynamics of complex physical systems
• interest in using statistical learning to infer dynamical models from data
• a productive and collegiate attitude to working in diverse interdisciplinary teams.