Postdoctoral Research Associate in fair machine learning and large language models.
Carslaw Building (F07), Australia
Full Time Mid-level / Intermediate USD 105K - 116K
The University of Sydney
The University of Sydney: A global top 20 university in Sydney, Australia, leading the way in addressing environmental, social, and governance challenges. Ranked 11th in the world for sustainability.Full time, 2-year fixed term opportunity, located at the School of Mathematics and Statistics on the Camperdown Campus
Opportunity to contribute to fair/trustworthy Machine Learning at the University of Sydney
Base Salary, Academic level A $105,314 - $116,679 p.a + 17% superannuation
About the opportunity
The School of Mathematics and Statistics is currently seeking a Postdoctoral Research Associate in fair machine learning and large language models.
Your key responsibilities will be to:
work on the ARC DP project on theory and algorithms for fair (trustworthy) machine learning and large language models (LLM)
work on the theoretical analysis and the design of efficient optimization algorithms for fair machine learning models and post-training LLMs which aligned with human values
conduct extensive simulation and experiments on real-world applications
help with academic communications with industrial collaboration partners.
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, data science or a closely related area
an excellent track record of publishing high-quality papers in top-tier machine learning conferences and journals
research experience in machine learning, deep learning and optimization
research experience in machine learning, deep learning or large language models
strong math/statistics background
solid programming skills.
Pre-employment checks
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.
EEO statement
At the University of Sydney, our shared values are trust, accountability and excellence and we strive to be a place where everyone can thrive. We are committed to creating a University community that thrives through diversity and reflects the wider community that we serve. We deliver on this through our commitment to diversity and inclusion, evidenced by our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTIQ+. We welcome applications from candidates from all backgrounds.
We are proud to be recognised as an Australian Workplace Equality Index (AWEI) Gold employer. Find out more about our work on diversity and inclusion.
How to apply
Applications (including a cover letter, CV, and any additional supporting documentation) can be submitted via the Apply button at the top of the page.
For employees of the University or contingent workers, please login into your Workday account and navigate to the Career icon on your Dashboard. Click on USYD Find Jobs and apply.
For a confidential discussion about the role, or if you require reasonable adjustment or any documents in alternate formats, please contact Simon Drew Recruitment Operations by email to recruitment.sea@sydney.edu.au
© The University of Sydney
The University reserves the right not to proceed with any appointment.
Click to view the Position Description for this role.
Applications Close
Sunday 29 June 2025 11:59 PMTags: Deep Learning Industrial LLMs Machine Learning Mathematics ML models PhD Research Statistics
Perks/benefits: Conferences
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