Hiring.Camp

Research Fellow

University of Sydney Career Site

·

Today

Location
The School of Information Technologies (J12), Australia
Type
Full-time
Department
Education
Education
PhD
Closing date
Today
Source
Workday

Description

  • Full time, 2 year fixed term position. Located on the Camperdown Campus, University of Sydney

  • Opportunity to contribute to the recently established Centre for Sustainability, AI and Life Sciences (SAILS) at the Faculty of Engineering

  • Base Salary Academic Level A $117,936 + 17% superannuation 

About the opportunity

The Centre for Sustainability, AI and Life Sciences (SAILS) brings together AI researchers and domain experts from across the University of Sydney, covering a broad spectrum of areas from molecular biology and health to chemistry and clean energy.

We are looking for Research Fellows to join the Centre to work closely with academics across disciplines on research projects within SAILS. In addition, you will be given the opportunity to publish and present your work at leading AI conferences and in the major journals of your application area, and to mentor HDR and Honours students.

Applications are welcome across the full breadth of AI for sustainability and the life sciences. We are particularly interested in:

  • machine learning for molecular and omics data, including representation learning for biological sequences and structures, and the integration of multiple omics layers

  • machine learning combined with first principles and multiscale simulation for the design of molecules, catalysts and materials, with applications in clean energy and decarbonisation

  • AI for clinical and health research using heterogeneous data (free text, structured records, images, audio), including locally hosted and fine-tuned large language models

  • computer vision for biological and medical imaging, including three-dimensional, spatial and temporal image data

  • trustworthy AI for sensitive and distributed data, including privacy-preserving and federated learning, uncertainty quantification, and efficient real-time inference in resource-constrained settings

Your key responsibilities will be to:

  • conduct high-quality research independently and collaboratively to advance the state-of-the-art in AI and its application to sustainability and the life sciences

  • publish research outcomes in leading international conferences and journals

  • collaborate with researchers across disciplines

  • adhere to and promote the University's health, safety and ethical guidelines.

About you

Successful applicants will have:

  • a PhD (or near completion) in computer science, statistics, engineering, or a physical, environmental or life science discipline

  • demonstrated expertise in AI and machine learning, including experience building and evaluating models in frameworks such as PyTorch, and running workflows in HPC environments

  • experience applying machine learning to scientific problems, ideally in a sustainability or life sciences domain

  • proven capability for independent research, evidenced by high-quality publications

  • excellent interpersonal and communication skills, including the ability to work with collaborators across disciplines

  • commitment to fostering an inclusive and respectful workplace, and an understanding of and adherence to University policies and procedures related to health and safety.

Pre-employment checks

Your employment is conditional upon the successful completion of all pre-employment or background checks required for the role in terms satisfactory to the University.  Also, to meet the University’s obligations under the National Higher Education Code to Prevent and Eliminate Gender-Based Violence you will be asked to declare if you have been investigated for, or found to engaged in, sexual harm or gender-based violence in the course of previous employment or in a legal process. 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 LGBTQIA+. We welcome applications from candidates from all backgrounds. 

We are proud to be recognised as an Australian Workplace Equality Index (AWEI) Platinum 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 Liam Newson and Nicole Feain, Recruitment Operations by email to [email protected]

© 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

Monday 28 September 2026 11:59 PM

Skills

Machine LearningComputer VisionPyTorchWorkday

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