Organisation/Company UNIVERSITY OF SYDNEY Research Field Computer science Mathematics Environmental science Geosciences Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1) Application Deadline 28 Sep *********:00 (UTC) Country Australia Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
Offer Description
Full time, 2 year fixed term position. Located on the Camperdown Campus, University of Sydney
Chance 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.
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.
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
The University reserves the right not to proceed with any appointment.
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📌 Research Fellow, Centre For Sustainability, Ai And Life Sciences (Sydney)
🏢 Times Higher Education
📍 Sydney