Postdoctoral Fellow

Classification: Academic Level A 
Salary package: $91,546 - $114,906 per annum plus 17% superannuation

Terms: Full time, Fixed term (up to 2 years)

• Be part of a nationally funded, high-impact research project
• Collaborate with leading researchers across ANU, UNSW, and Macquarie University
• Work in a vibrant, interdisciplinary research environment at one of Australia’s top universities
• Contribute to research with real societal impact, shaping fair and transparent decision-making systems

The position

The Research School of Finance, Actuarial Studies and Statistics (RSFAS) in the ANU College of Business and Economics (CBE) invites applications for a Postdoctoral Fellow (Academic Level A) on a full time fixed-term appointment of 2 years, commencing in January 2027 or as soon as possible thereafter.  The Postdoctoral Fellow will be located in the Acton Campus in Canberra, Australia. The position is offered in connection with the ARC Discovery Project grant “Responsible Statistical Learning: Uncertainty, Fairness and Transparency”.

The successful candidate will play a key role in advancing high-quality research under the ARC Discovery Project led by Associate Professor Yanrong Yang (ANU), with collaborators Associate Professor Fei Huang (UNSW Sydney) and Professor Samuel Muller (Macquarie University).

Reporting to Associate Professor Yang, the Postdoctoral Fellow will contribute to cutting-edge research, developing statistical methodology and theory related to the primary aims and themes of the Discovery Project. In particular, the Postdoctoral Fellow will aim to build the theory that quantifies the trade-off between fairness level and statistical accuracy within a fundamental statistical framework. The initial work starts from the motivation of gender-fair insurance pricing. As appropriate, the Postdoctoral Fellow will also collaborate with other researchers to develop scalable computational algorithms and translate the proposed methodology into practical applications.

We are seeking applications from candidates with either a track record or proven potential in research in Statistics and/or Statistical Science.  It is anticipated that the successful candidate will have, or be close to obtaining, a PhD in Statistics (or in a related discipline of relevance to the Discovery Project).  For a successful candidate who has not already been awarded a PhD, it is required that the thesis has already been submitted before taking up employment.

As Australia's leading university, the ANU seeks to advance knowledge through internationally-leading research and teaching. We contribute to science, medicine, industry and government by conducting world-class, long-term strategic research, and through the provision of a range of specialised undergraduate and postgraduate degree programs.

CBE provides an excellent educational experience for our students. Our global alumni network reaches the world's leading companies, policy agencies and universities. The way we operate is guided by our Values and Behaviours and we encourage you to apply if you are looking for a workplace that encourages respect, collegiality and excellence.

For further information, please contact Associate Professor Yanrong Yang, E: Yanrong.Yang@anu.edu.au

ANU values diversity and inclusion and is committed to providing equal employment opportunities to those of all backgrounds and identities. For more information about staff equity at ANU, visit https://services.anu.edu.au/human-resources/respect-inclusion

Application information

In order to apply for this role please make sure that you upload the following documents:

• A statement addressing the selection criteria.
• A current curriculum vitae (CV) which includes the names and contact details of at least three referees (preferably including a current or previous supervisor). If your CV does not include referees you can complete these online when prompted in the application form.

Applications which do not address the selection criteria may not be considered for the position. 

Please note: The preferred candidate will be required to complete mandatory pre-employment declarations and background checks relevant to the role they have applied for, in accordance with the Background Checking Procedure and the National Higher Education Code to Prevent and Respond to Gender-Based Violence.