Research Fellow Federated & Multimodal Learning

Job No.: 695158

Location: Clayton campus

Employment Type: Full-time

Duration: 2-year fixed-term appointment

Remuneration: $123138 - $146228 pa Level B (plus 17% employer superannuation)

• Amplify your impact at a world top 50 University
• Join our inclusive collaborative community
• Be surrounded by extraordinary ideas - and the people who discover them

The Opportunity

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 Universitys 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

AtMonash work feels different. Theres a sense of belonging from contributing to something ground breaking a place where great things happen.

We value difference anddiversity and welcome and celebrate everyones contributions lived experience and expertise. Thats why we champion aninclusive and respectful workplace culture where everyone is supported to succeed.

Some 20000 staff work for Monash around the world. We have 95000 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 worlds best tertiary institutions. We rank in theworlds top-50 universities in rankings including the QS World University Rankings 2026.

Together with ourcommitment to academic freedom you will have access to quality research facilities infrastructure world-class teaching spaces and international collaboration opportunities.

Learn more about Monash.

Today we have themomentum to create the future we need for generations to come. Accelerate your change here.

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

Position Description:Research Fellow

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

Supporting a diverse workforce