Jobs and Careers

• Undertake cutting-edge collaborative research into Antarctic ice sheet science
• Use a unified statistical modelling framework to develop new understandings
• Full time, four-years fixed-term, based in Hobart

About the opportunity

This postdoctoral research position will develop and apply an optimal spatial statistical combination of multivariate datasets to contribute new knowledge of change in the mass of the East Antarctic Ice Sheet. The position is part of a new prestigious ARC Laureate Fellowship team of about 15 researchers who are being assembled to work together on tracking and predicting the future of the East Antarctic Ice Sheet. The successful candidate will bring their expertise in environmental spatial statistical science to improve understanding of the change and variability of the ice sheet. They will contribute to building a collegial and collaborative team research environment. Team researchers are well supported by travel and professional development funds. This is an opportunity to be part of a new and exciting team whilst working at the world’s leading Antarctic and Southern Ocean university.

What you’ll do:

• Undertake research in ice sheet science, publishing findings in international peer-reviewed journals, and assist in student supervision.
• Combine multiple satellite and field datasets in a unified statistical modelling framework to develop understandings of the East Antarctic Ice Sheet.
• Initiate and develop competitive external and other funding applications.
• Engage with professional development opportunities appropriate for an academic, government or industry career.
• Develop and maintain productive and effective links with discipline, interdisciplinary domains, profession, industry and the wider community.

­What we’re looking for:

• A PhD in geostatistics, spatial statistics, or commensurate discipline.
• Demonstrated ability to undertake research in spatial data analysis, including working with multivariate data.
• Substantial experience in code development and, preferably, experience with Bayesian statistical modelling techniques and software.
• Willing to develop expert knowledge of the East Antarctic Ice Sheet and a range of geodetic, field and model datasets.
• A record of contributing to building and maintaining effective and productive networks.

Salary details

Appointment to this role will be at Academic Level A and will have a total remuneration package of up to $125,877 comprising base salary within the range of $83,198 to $107,587 plus 17% superannuation.

How to Apply

• To apply online, please provide the following supporting documentation:
  • Resume
  • Cover letter outlining your suitability and motivation for the role
  • Your 1-2 paragraph responses to each of the success profile criteria from the Position Description below
• For further information about this position, please contact Matt King, Director, ARC Australian Centre for Excellence in Antarctic Science (ACEAS), matt.king@utas.edu.au or +61 3 6226 1974.
• Please visit https://www.utas.edu.au/jobs/applying for our guide to applying and details on the recruitment process.
• For current UTAS staff, in submitting your application, you acknowledge you have/intend to discuss your interest in this vacancy with your current manager and understand they may need to be contacted confidentially by the hiring manager as part of the assessment of your application.
• Please refer to the attached Position Description Below for full details.

 501599 - Position Description - Postdoctoral Fellow in Environmental Spatio-Temporal Statistics.pdf

Applications close Sunday, 30 November 2025, 11.55pm

 The University of Tasmania acknowledges the Palawa/Pakana and Gadigal/Wangal people as the traditional custodians of the land, sea and waters of the areas upon which we live and work. We recognise their valuable contributions and deep connection to country and pay respect to Elders past and present.

 As part of our commitment to a safe and inclusive workplace, employment history and police checks may be conducted as part of the selection process.