Organisation/Company UNIVERSITY OF SYDNEY Research Field Mathematics Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Application Deadline 27 Apr 2026 - 00:00 (UTC) Country Australia Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
Offer Description
* Full time, 2-year fixed term opportunity, located at the School of Mathematics and Statistics on the Camperdown Campus
* Opportunity to contribute to research on hybrid numerical-exponential asymptotic methods and their applications at the University of Sydney
* Base Salary, Academic level A $105,117 - $121,054 p.a + 17% superannuation
About the opportunity
The School of Mathematics and Statistics is currently seeking a Postdoctoral Research Associate in the development and application of hybrid numerical-asymptotic methods to nonlinear systems.
Your key responsibilities will be to:
* work on an ARC DP project aiming to develop of hybrid asymptotic methods based on exponential asymptotics and computational complex analysis
* apply these methods to applied nonlinear problems arising from water wave theory and nonlinear optics
* conduct research either independently or as part of a team
* contribute to journal publications and other academic outputs
* produce software implementations of the algorithms developed in this project.
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 mathematics, applied mathematics, computational mathematics or a closely related discipline
* a strong background in asymptotic analysis, particularly including exponential asymptotics, resurgence, or asymptotics beyond-all-orders
* a strong background in numerical analysis, particularly computational complex analysis
* an excellent track record of publishing high-quality papers in top-tier mathematics journals
* solid mathematical programming skills.
Your employment is conditional upon the completion of all role required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment.
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