AI-Driven Prediction of Scaffold Performance for Bone Regeneration

Summary

Join a Leading Interdisciplinary Research Group at the University of Sydney to Advance Regenerative Medicine Using AI.

The University of Sydney’s School of Computer Science and School of Biomedical Engineering are jointly seeking a highly motivated PhD student to work on an innovative project at the interface of artificial intelligence and biomedical engineering. This interdisciplinary research will harness multi-modal data and creative AI techniques to predict the regenerative potential of biomaterial scaffolds, with the goal of accelerating the development of novel treatments for bone defects.

Supervisor

Professor Hala Zreiqat.

Research location

Biomedical Engineering

Synopsis

The project, co-supervised by Prof. Zhiyong Wang (Computer Science) and Prof. Hala Zreiqat (Biomedical Engineering) and A/Prof Zufu Lu, is at the forefront of AI applications in regenerative medicine. It will investigate advanced deep learning techniques to predict cell fate and scaffold outcomes using temporal omics and imaging data.

The key research components include:

• Multi-level performance evaluation to minimize overfitting and improve model generalizability using in-silico and independent public datasets.
• Modelling of morphological and molecular changes during cell differentiation using AI-based temporal modelling and evolving neural networks.
• Prediction of scaffold performance in bone regeneration using multi-modal data integration and generative AI.

This work will contribute to transforming how biomaterial scaffolds are designed and assessed, with broad implications for regenerative therapies and personalized medicine. 

This opportunity is only open to students who receive a Research Training Program (RTP) Scholarship.

The successful candidate must:

• Have a Honours degree (First Class or First Class Honours Equivalent) or a Master's degree with a substantial research component in computer science, biomedical engineering, bioinformatics, data science, or a related field.
• Have strong programming and analytical skills (e.g., Python, deep learning frameworks).
• Demonstrate research aptitude and excellent communication skills in English.
• Show a keen interest in interdisciplinary research at the interface of AI and biology. Previous research experience, including thesis or project work in relevant areas, is desirable.

Outstanding final-year undergraduate students who expect to graduate this year with first-class honours are encouraged to apply, and commencement of the position can be arranged upon completion of their degree.

Successful applicants will have access to:

• Cutting-edge experimental and computational facilities.
• Interdisciplinary supervision and mentoring.
• Funding to present at national and international conferences.

How to apply:

Please email  zhiyong.wang@sydney.edu.au and hala.zreiqat@sydney.edu.au / zufu.lu@sydney.edu.au with the following:

• A brief cover letter expressing your interest and suitability.
• Your CV, including academic transcripts and details of any research experience.

Expressions of interest will be reviewed on a rolling basis until the position is filled.

Want to find out more?

Opportunity ID

The opportunity ID for this research opportunity is 3660

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