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Medical AI Exploration with Machine Learning and Robotics

Primary supervisor

Zongyuan Ge

PhD Studentship Description:

The studentship will be based at Monash University Monash Medical AI Group led by Associate Professor Zongyuan Ge. The successful candidate will join a multi-disciplinary team of clinician scientists and computer scientists to develop diagnosis/predictive/treatment/robotics surgery models of diseases of interest using multimodal medical data, consisting of images, report, genomics, and physiological data. The project will provide an ideal opportunity for any talented and motivated individual to develop technical skills and gain practical experiences in cutting-edge areas of research. Various internship opportunities at NVIDIA, IBM, Centre for Eye Research Australia, Eyetelligence and Airdoc will be supported during Ph.D. study. Bridging program during VISA application will be provided if shortlisted (Research assistant and supported visiting program).

 The Aim

This study centres on how computer-based decision procedures, under the broad umbrella of artificial intelligence (AI), can assist in improving health and health care. Radiology images, e.g. X-rays, fundus image, dermascopic image, MRI, CT-scans and EHR, form the basic screening and diagnosis procedure for many diseases of interest. The goal of this project is to develop computational models using text and images (and possibly other data modalities) to help medical experts to improve the quality of patient care. 

Scientific Contribution

Our group has strong publication record of 100+ first or senior author top-tier (ERA ranking A*/A) journals and technical conferences in the machine learning and medical AI field. His research papers have been published in top-tier journals and conferences such as The Lancet Digital Health (IF=36.615), The British Medical Journal (IF=96.22), JAMA Neurology (IF=29.91), Nature Nanotechnology (IF=39.21), Brief in Bioinformatics (IF=11.62), Hypertension (IF=10.19), IEEE Transactions on Pattern Analysis and Machine Intelligence (IF=24.31), IEEE Transactions on Medical Imaging (TMI) (IF=10.048), Medical Imaging Analysis (IF=13.83) and top-tier conference including NeurIPS, ICLR, CVPR, ICCV, ECCV, KDD, AAAI, IJCAI and MICCAI.


MMAI Direction


Required knowledge

  • Research experience in AI, data science, robotics, computer science or a related field (having medical background would be a plus)
  • Experience in statistics/computer vision/machine learning/robotics
  • Outstanding academic output documented via journal/conference publications in the relevant fields
  • Ability to program in either Python or C++ or any computer programming language
  • Outstanding communication skills with fluency in both written and spoken English
  • We support Women in STEM

Project funding

Project based scholarship

Learn more about minimum entry requirements.