PhD in Explainable AI to Understand Respiratory Diseases and Treatment Effect

Thursday 21st October 2021

Organization Australian Institute for Machine Learning, The University of Adelaide

Location Adelaide, Australia

Title PhD in Explainable AI to Understand Respiratory Diseases and Treatment Effect

URL https://cs.adelaide.edu.au/~gabriel/

Email Address gabriel.maicas@adelaide.edu.au

Description The Women's and Children's Hospital (WCH) and The Australian Institute for Machine Learning (AIML) have established a strategic collaboration with the main focus on developing machine learning (ML) algorithms to improve health outcomes and health care.

X-ray Velocimetry (XV) is a revolutionary lung imaging technology developed by 4DMedical. XV enables lung motion to be tracked over time, and airflow to be calculated at any point in the airway tree. This allows the location and intensity of lung disease, and its resolution with treatment, to be measured. Functional XV measurements can be acquired with far lower radiation doses than conventional low-dose CT structural imaging methods.

This PhD project is designed to develop new machine-learning based approaches to interrogating the XV data. Data obtained from XV imaging is rich in detail that is yet to be properly exploited. This PhD aims to design novel explainable machine learning algorithms to gain insight about lung diseases. We expect that the project will impact both the medical and the machine learning communities by finding new markers for lung disease from XV and improving fairness and outcomes of machine learning models.

The research will be hosted at the Australian Institute for Machine Learning (Australia’s premier research institution in artificial intelligence, machine learning and computer vision) and The Respiratory X-ray Imaging Lab (ReXIL) to promote cross-fertilization. ReXIL is the University of Adelaide member of the Australian Lung Health Initiative (ALHI), who were the recent recipients of a $29 Million Medical Research Future Fund grant.

The ideal candidate will have a strong interest in medical machine learning (experience is preferable), strong scientific interest, strong programming skills (Python, Matlab, Pytorch, etc...), and highly motivated and ability to work independently and in collaboration with an interdisciplinary team. The selected candidate will be required to apply to apply to the University of Adelaide scholarship by October 31st.

For further information regarding this position, contact:

Dr. Gabriel Maicas AI Lead for Women's and Children's Hospital (North Adelaide) Australian Institute for Machine Learning, The University of Adelaide