• One of Australia’s leading research & teaching universities
• Vibrant campus life with a strong sense of community & inclusion
• Enjoy a career that makes a difference by collaborating & learning from the best

At UNSW, we pride ourselves on being a workplace where the best people come to do their best work.

THIS ROLE IS LOCATED IN SYDNEY, AUSTRALIA.

The School of Mathematics and Statistics currently has more than ninety continuing academic staff and several dozen research staff as well as visiting academics. UNSW is the only university in Australia to be ranked in the top 100 in the world in mathematics and statistics by each of the three ranking bodies: CWTS Leiden, USNews and QS.

This position is based in the School of Mathematics and Statistics in the Faculty of Science and supports the Australian Research Council funded Discovery Project: Fixing the holes in Bayesian model comparison. This role will develop new fundamental theory in Bayesian model comparison, and create fast and scalable methods for its implementation, building on techniques from computational statistics and machine learning.

The Postdoctoral Fellow (Level B) is expected to carry out independent and/or team research within Bayesian inference and computation and to carry out activities to develop their research expertise relevant to this field.

About the role

• Level B - $127K - $150K plus 17% Superannuation and annual leave loading
• Fixed term – 3 years
• Full-time (35 hours per week)

Specific responsibilities for this role include:

• Engage in individual and/or collaborative research in a manner consistent with disciplinary practice.
• Create scholarly impact in the discipline which is recognised by peers in the advancement of disciplinary knowledge, including publishing research papers in high quality statistics and machine learning journals and conference proceedings, and the preparation and release of supporting open-source software.
• Conduct research/scholarly activities under limited supervision, either independently or as a member of a team, including attending and presenting research in seminars and conferences, and organising research events.
• Establish a personal research portfolio and start developing independent research proposals.
• Contribute to the development of applications for competitive funding under the guidance of senior colleagues, where appropriate.
• Mentor and guide students and colleagues and develop the next generation of academics through involvement in supervision of HDRs and other research students, as merited.
• Teach appropriate courses in Statistics and Data Science, should the opportunity arise, and by mutual agreement.
• Align with and actively demonstrate the Code of Conduct and Values.
• Cooperate with all health and safety policies and procedures of the university and take all reasonable care to ensure that your actions or omissions do not impact on the health and safety of yourself or others.

About the successful applicant
(Selection Criteria)

To be successful in this role you will have:

• A PhD in Bayesian statistics and computation.
• Knowledge of, and research experience in, several of the following areas: Bayesian statistical theory; Bayesian model comparison; Monte carlo algorithms for posterior simulation (e.g. MCMC, SMC, etc); variational inference; transdimensional algorithms (Monte carlo methods, variational inference, etc) for Bayesian model comparison; generalised Bayesian inference.
• Proven commitment to proactively keeping up to date with discipline knowledge and developments.
• Demonstrated track record in research with outcomes of high quality and high impact with clear evidence of the desire and ability to continually achieve research excellence as well as the capacity for research leadership.
• A track record of significant involvement with the profession.
• High level communication skills and ability to network effectively and interact with a diverse range of students and staff.
• Demonstrated ability to work in a team, collaborate across disciplines and build effective relationships.
• Evidence of highly developed interpersonal and organisational skills.
• An understanding of and commitment to UNSW’s aims, objectives and values in action, together with relevant policies and guidelines.
• Knowledge of health and safety responsibilities and commitment to attending relevant health and safety training.

You should provide a cover letter and systematically address the selection criteria listed within the position description in your application.

For informal queries, please see the below contact details. 

Otherwise, please apply online - applications will not be accepted if sent directly to the contact listed.

Contact:
Scott Sisson
E: scott.sisson@unsw.edu.au
Applications close: June 10^th, 2026

Find out more about working at UNSW at www.unsw.edu.au

UNSW is committed to equity diversity and inclusion. Applications from women, people of culturally and linguistically diverse backgrounds, those living with disabilities, members of the LGBTIQ+ community; and people of Aboriginal and Torres Strait Islander descent, are encouraged. UNSW provides workplace adjustments for people with disability, and access to flexible work options for eligible staff. The University reserves the right not to proceed with any appointment.