Research Fellow - Federated & Multimodal Learning
Monash•Clayton, NC
•Hybrid
About The Position
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.
Requirements
- Driven post doctoral researcher with a passion for applying advanced machine learning to real-world medical challenges
- Strong technical foundation in AI methodologies
- Thrive in collaborative, multi-disciplinary environments
Responsibilities
- 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
Benefits
- Flexible and hybrid working arrangements
- Support for parents
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
