Research Assistant

About The Team

The School of IT is well resourced with research and teaching facilities and hosts several research groups with strengths in the areas of Business Information Systems, Artificial Intelligence, Data Analytics, Virtual Reality and Information Technology with application across defence, agricultural sciences, medical, biosecurity and other related areas.

Your New Role

As a Research Officer, you will support a research project, "Exploring Causal Learning through Graph Neural Networks (GNN) and Large Language Models (LLM)", funded by

School of Information Technology Seed grants for Early Career Research (ECR) scheme.

In this role, you will collaborate with the project team to support literature research, conduct experiments, manage data, undertake data analysis, draft research papers and other documentation and tasks associated with the project "Exploring Causal Learning through Graph Neural Networks (GNN) and Large Language Models (LLM)".

Your Key responsibilities will include -

• Conduct literature reviews, identify research gaps, and assist in hypothesis development and experimental design
• Source and prepare datasets, develop and test GNN and LLM models, and analyse results using Python-based tools
• Supporting academic writing, prepare technical reports and presentations, and maintain organised records of project progress

Please refer to the Position Description for further details.

What We Offer You

This casual role attracts a competitive casual rate of $57.13 p/hr - $61.73 p/hr inclusive of 25% casual loading plus 12% employer superannuation contributions.

You'll join a dynamic and talented team where diversity and innovation thrive. Our Silver-tier status in the Australian Workplace Equality Index (AWEI), awarded in 2025, reflects our commitment to LGBTIQA+ inclusion, equity, and creating a safe, welcoming environment for all. We strive to be the university of choice for First Nations peoples, honouring Indigenous knowledge. Sustainability is central to our community and guided by clear, confident leadership, we are working toward an ambitious future with goals of net zero emissions and zero waste by

As well as the flexibility to maintain a work life balance, our staff enjoy a vibrant, natural campus with world-class facilities, along with a variety of benefits, including:

• Periodic wage increases between 1 January 2026 to 1 July 2026 totalling an 4% increase
• Employee Assistance Program
• On-campus services and facilities, such as a Childcare Centre, Gym, Vet Hospital, and Chiropractic Clinic

For further information, check out our benefits and services page

Join us

Please apply online via the Apply Now button, along with submitting the following documents to support your application -

• A cover letter including a statement addressing the selection criteria (with reference to the Position Description)
• Your most recent resume (CV)

What you'll bring to the role:

• Currently enrolled in or recently completed a Masters or higher degree in Computer Science, Data Science, Artificial Intelligence, or a related discipline.
• Demonstrated experience in Python programming, including use of libraries such as PyTorch, TensorFlow, and/or HuggingFace Transformers.
• Solid understanding of core machine learning principles.
• Basic understanding of graph neural network concepts.
• Familiarity with large language models and their applications in natural language processing tasks.

Applicants should refer to the Position Description for further details on the work requirements, duties, skills and experience required for this role. Applications sent by post or email will not be accepted.

Please note visa sponsorship is not available for this position. Applicants are expected to have current and valid work rights in Australia

Please see the Applicant Guide for more information. Applicants who have support or access requirements, are encouraged to advise this at the time of their application, to ensure appropriate assistance is provided throughout the recruitment process.

Contact Us

For enquiries about the opportunity on offer please reach out to Shikha Anirban, Lecturer in Information Technology, and quote JR104213 as the reference.

Applications Close on 05/08/ :59pm AWST)

The University reserves the right to withdraw this advertisement at any time.

Murdoch University acknowledges the different perspectives, skills and experience that people from different backgrounds bring to strengthen its workforce. Murdoch University is committed to enhancing diversity in all its forms and strongly encourages suitably qualified candidates from Aboriginal and/or Torres Strait Islander peoples, women, people with disability, people of CaLD background and people of diverse genders to apply for this important position.