Research Supervisor Connect

Data-intensive solutions for medical technologies

Summary

This project aims at developing advanced solutions in software for processing medical data, addressing the issue of less or no labelled data.

Supervisor

Associate Professor Omid Kavehei.

Research location

Biomedical Engineering

Synopsis

Using today's advances in machine intelligence and pattern recognition, and our incredibly massive amount of structured and unstructured data on central nervous systems and the Brain, making sense of massive datasets with high amount of data-noise and incoherency is now a possibility [1-3]. We will develop, test and implement cognitive computing technologies in data-driven medical contexts. This project aims to develop data-driven machine learning medical technologies to make medical practices more personalized and precision in both domains of medical devices and services. While expanding knowledge in the information and computing sciences, this project aims to massively reduce costs in health and support services as well as providing low-cost bed-side or wearable technologies for constant monitoring and notification systems. This project uses our state-of-the-art GPU cluster to develop these technologies.

Additional information

How to Apply:

To apply, please email omid.kavehei@sydney.edu.au with the subject line “PhD Application”, and attach the following:

  • CV
  • Transcripts

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Opportunity ID

The opportunity ID for this research opportunity is 3496

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