PhD Scholarship in Multimodal Federated Learning and Medical Image Analysis
PhD Scholarship in Multimodal Federated Learning and Medical Image Analysis
Job No.
:******
Location:Clayton campus
Employment Type:Full-time
Duration:3-year and 3-month fixed-term appointment
Remuneration:$37,145 (tax-free RTP stipend)
For scholarship procedures and conditions, please see: graduate-research/future-students/scholarships/scholarship-policy-and-procedures.
The Faculty will provide the tuition fee scholarship and Single Overseas Health Cover (OSHC) for the successful international awardee.
The Chance
Expressions of interest are sought from outstanding candidates for PhD study in theDepartment of Data Science and Artificial Intelligence at the Faculty of IT, Monash University.
As part of this scholarship, the successful candidate will develop novel federated learning and multimodal deep learning models for healthcare.
The project will focus on enabling privacy-preserving learning from distributed healthcare data sources, including longitudinal medical imaging, electronic health records, pathology, and other clinical data.
The candidate will investigate novel approaches for multimodal representation learning, foundation model adaptation, and federated learning to improve disease diagnosis, risk prediction, and clinical decision support.
Applications will include chronic diseases such as cancer, diabetes, and rheumatoid arthritis.
This research forms part of the National Infrastructure for federated learNing in DigitAl health (NINA), a national initiative aimed at advancing privacy-preserving AI infrastructure and analytics for healthcare across Australia.




The candidate will be supervised by Dr Yasmeen George (******), and will work closely with collaborators across medicine, healthcare organisations, and industry partners.
Candidate Requirements
As the successful candidate, you will:
Have a relevant Honours or Masters degree with H1 or equivalent;
Meet the eligibility criteria for PhD candidature at Monash University.
You can check the minimum entry requirements for thePhD.
Applicants must also satisfyMonash'sEnglish Language Proficiencyrequirements;
Demonstrate knowledge of machine learning, medical image analysis, computer vision, federated learning, foundation models, adaptation techniques, multimodal learning, longitudinal image analysis or related areas, evidenced through coursework, research projects or publications;
Have experience with Python programming and the use of high-performance computing infrastructure for AI research;
Have excellent written and verbal communication skills;
Have the ability to work independently, as well as part of a team;
Have the ability to plan, organise, manage multiple tasks and meet deadlines;
Have analytical thinking, data analysis and critical problem-solving skills; and
Be enrolled full time and on campus.
Applicants who already hold a PhD will not be considered.
Enquiries:Dr Yasmeen George, ******
Applications Close:Monday 31 August ****, 11:55pm AEST
Supporting a diverse workforce
Monash University recognises that its Australian campuses are located on the unceded lands of the people of the Kulin nations, and pays its respects to their elders, past and present.
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📌 Phd Scholarship In Multimodal Federated Learning And Medical Image Analysis (South Australia)
🏢 Monash
📍 South Australia