Job Description
Location
Sydney NSW
Full job description
Job no: 533540
Work type: Full Time
Location: Sydney, NSW
Categories: Post Doctoral Research Associate
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.
The School of Mathematics and Statistics currently has more than eighty continuing academic staff and more than thirty 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 CWTS Leiden, US News and QS. The School embodies a broad range of research interests in the areas of applied and pure mathematics, and statistics.
The Research Associate will undertake collaborative and self-directed research on an ARC-funded Discovery Project titled “High Dimensional Approximation, Learning, and Uncertainty”. The aim of the project is to devise and apply innovative schemes for high-dimensional approximation. These schemes will be of proven reliability and accuracy, able to handle variables or uncertain parameters numbering in the hundreds or more, fast in execution, and tailored to specific applications.
THIS ROLE IS BASED IN SYDNEY, AUSTRALIA.
About the role
Level A - $113K - $121K plus 17% Superannuation and annual leave loading
Fixed Term – 2 years
Full-time (35 hours per week)
The role reports to Professor Frances Kuo and Professor Ian Sloan and has no direct reports.
Specific responsibilities for this role include:
Conduct research in the area of High Dimensional Approximation, Uncertainty Quantification, Deep Learning, and Quasi-Monte Carlo Methods independently and as part of a team, including leading some areas of the project where the opportunity arises and where appropriate.
Contribute to the writing of scientific papers and reports for international journals and progress reporting to other researchers and industry partners.
Assist with the coordination of research activities and actively contribute to research outputs to meet project milestones.
Contribute to the preparation of research proposal submissions to funding bodies and actively seek collaboration with industry partners as appropriate.
Participate in and/or present at conferences and/or workshops relevant to the project as required.
Joint supervision of honours and HDR students.
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 Mathematics, preferably in computational mathematics or related area.
Demonstrated ability to conduct independent research with limited supervision.
Strong interpersonal skills with demonstrated ability to communicate and interact with a diverse range of stakeholders and students.
Demonstrated knowledge in Quasi-Monte Carlo methods and/or finite element analysis and/or machine learning is highly desirable.
Strong computer programming experience, preferably with Matlab, C++, or Python.
Demonstrated ability to work in a team, collaborate across disciplines and build effective relationships.
Evidence of highly developed interpersonal skills.
Demonstrated ability to communicate and interact with a diverse range of stakeholders and students.
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 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:
Frances Kuo
E: [email protected]
Applications close: August 8th, 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.
Position Description
Advertised: 11 Jul 2026 AUS Eastern Standard Time
Applications close: 08 Aug 2026 AUS Eastern Standard Time
Sydney NSW
Full job description
Job no: 533540
Work type: Full Time
Location: Sydney, NSW
Categories: Post Doctoral Research Associate
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.
The School of Mathematics and Statistics currently has more than eighty continuing academic staff and more than thirty 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 CWTS Leiden, US News and QS. The School embodies a broad range of research interests in the areas of applied and pure mathematics, and statistics.
The Research Associate will undertake collaborative and self-directed research on an ARC-funded Discovery Project titled “High Dimensional Approximation, Learning, and Uncertainty”. The aim of the project is to devise and apply innovative schemes for high-dimensional approximation. These schemes will be of proven reliability and accuracy, able to handle variables or uncertain parameters numbering in the hundreds or more, fast in execution, and tailored to specific applications.
THIS ROLE IS BASED IN SYDNEY, AUSTRALIA.
About the role
Level A - $113K - $121K plus 17% Superannuation and annual leave loading
Fixed Term – 2 years
Full-time (35 hours per week)
The role reports to Professor Frances Kuo and Professor Ian Sloan and has no direct reports.
Specific responsibilities for this role include:
Conduct research in the area of High Dimensional Approximation, Uncertainty Quantification, Deep Learning, and Quasi-Monte Carlo Methods independently and as part of a team, including leading some areas of the project where the opportunity arises and where appropriate.
Contribute to the writing of scientific papers and reports for international journals and progress reporting to other researchers and industry partners.
Assist with the coordination of research activities and actively contribute to research outputs to meet project milestones.
Contribute to the preparation of research proposal submissions to funding bodies and actively seek collaboration with industry partners as appropriate.
Participate in and/or present at conferences and/or workshops relevant to the project as required.
Joint supervision of honours and HDR students.
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 Mathematics, preferably in computational mathematics or related area.
Demonstrated ability to conduct independent research with limited supervision.
Strong interpersonal skills with demonstrated ability to communicate and interact with a diverse range of stakeholders and students.
Demonstrated knowledge in Quasi-Monte Carlo methods and/or finite element analysis and/or machine learning is highly desirable.
Strong computer programming experience, preferably with Matlab, C++, or Python.
Demonstrated ability to work in a team, collaborate across disciplines and build effective relationships.
Evidence of highly developed interpersonal skills.
Demonstrated ability to communicate and interact with a diverse range of stakeholders and students.
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 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:
Frances Kuo
E: [email protected]
Applications close: August 8th, 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.
Position Description
Advertised: 11 Jul 2026 AUS Eastern Standard Time
Applications close: 08 Aug 2026 AUS Eastern Standard Time
💡 Quick Summary
Seeking a career-building opportunity? The Research Associate - Mathematics and Statistics position is now open for candidates interested in the Education Jobs sector. This role in Sydney offers a professional environment and growth potential.
Requirement Snapshot: Candidates should possess basic communication skills, a proactive attitude, and the ability to work in a team. Experience in Education Jobs is a plus.
