Research Fellow – Federated & Multimodal Learning Full-time

Research Fellow – Federated & Multimodal Learning

Join the Department of Data Science and Artificial Intelligence as a Research Fellow and play a leading role in advancing artificial intelligence research for healthcare. This position will be part of the National Infrastructure for federated learNing in DigitAl health (NINA) initiative and will drive high-quality research in federated and multimodal learning, with a particular focus on foundation models, medical image analysis, and multimodal healthcare data integration.

In this role, you will:

• Develop novel federated AI methodologies, foundation model adaptation techniques, and multimodal deep learning approaches that enable privacy-preserving learning across distributed healthcare data sources
• Support health outcomes with research in transformative applications in diabetes, cancer, rheumatoid arthritis, and osteoarthritis, including disease diagnosis, risk prediction, and clinical decision support
• Establish scalable, privacy-preserving federated learning infrastructure to unlock the value of distributed health data and improve outcomes for Australians living with chronic diseases
• Contribute to the University's research excellence through high-quality publications, collaborative research partnerships, supervision of research students, and the development of competitive research funding opportunities

The successful candidate will be a driven post doctoral researcher with a passion for applying advanced machine learning to real-world medical challenges. If you thrive in collaborative, multi-disciplinary environments and possess a strong technical foundation in AI methodologies then apply today!

About Monash University

At Monash, work feels different. There's a sense of belonging, from contributing to something ground breaking – a place where great things happen. We value difference and diversity, and welcome and celebrate everyone's contributions, lived experience and expertise. That's why we champion an inclusive and respectful workplace culture where everyone is supported to succeed.

Some 20,000 staff work for Monash around the world. We have 95,000 students, four Australian campuses, and campuses in Malaysia and Indonesia. We also have a major presence in India and China, and a significant centre and research foundation in Italy. In our short history, we have skyrocketed through global university rankings and established ourselves consistently among the world's best tertiary institutions. We rank in the world's top-50 universities in rankings including the QS World University Rankings 2026. Together with our commitment to academic freedom, you will have access to quality research facilities, infrastructure, world-class teaching spaces, and international collaboration opportunities.

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Monash supports flexible and hybrid working arrangements. We have a range of policies in place enabling staff to combine work and personal commitments. This includes supporting parents.

To Apply

For instructions on how to apply, please refer to 'How to apply for Monash Jobs'. Your application must address the Key Selection Criteria. Diversity is one of our greatest strengths at Monash. We encourage applications from Aboriginal and Torres Strait Islander people, culturally and linguistically diverse people, people with disabilities, neurodivergent people, and people of all genders, sexualities, and age groups. We are committed to fostering an inclusive and accessible recruitment process at Monash. If you need any reasonable adjustments, please contact us at hr-recruitment@monash.edu in an email titled 'Reasonable Adjustments Request' for a confidential discussion. Your employment is contingent upon the satisfactory completion of all pre-employment and/or background checks required for the role, as determined by the University.

Enquiries: Dr Yasmeen George, Senior Lecturer, Department of Data Science and Artificial Intelligence, Faculty of Information Technology, yasmeen.george@monash.edu

Position Description: Research Fellow

Applications Close: Monday 31 August 2026, 11:55pm AEST