AI in the detection and diagnosis of preclinical and early osteoarthritis

Knee osteoarthritis (OA) affects more than 100 million people globally - a major cause of pain and disability costing Australia 2 billion dollars annually. AI applied to medical imaging technologies (X-ray and MRI) could allow clinicians to detect, quantify and monitor early cartilage changes and enable treatment and strategies for OA before structural and functional deficits become irreversible. CSIRO, UQ and Siemens Healthineers have developed machine learning algorithms for measuring knee cartilage (recently implemented into Siemens machines). This PhD project will investigate, develop and validate novel Deep learning algorithms for the detection and early diagnosis of OA. This that will improve the accuracy of the assessment and adapt it for use with several new MR modalities designed to assess cartilage microstructure.

The candidate will have the opportunity to work with a team of leading researchers from CSIRO, UQ and Siemens Healthineers in the areas of AI and medical imaging. You will also have access to state-of-the-art high-performance computing facilities across Australia through CSIRO and UQ for building AI models.

This project is supported by the CSIRO Industry PhD Scholarship.

This scholarship includes:

• living stipend of $47,000 AUD, indexed annually, and $13,000 p.a. for project operating and student development expenses
• tuition fees covered.

Learn more about the CSIRO Industry PhD Scholarship.

The stipulated CSIRO eligibility requirements are:

• be an Australian or New Zealand citizen, or Australian permanent resident
• meet university PhD admission and English language requirements
• have not previously completed a PhD
• not be in receipt of another primary scholarship
• be able to commence the program in the year of the offer
• enrol as a full-time PhD student
• be located at the agreed project location(s), and, if required, comply with the university’s external enrolment procedures.

You must contact the principal supervisor for this project to discuss your interest. You should only complete the online application after you have reached agreement on supervision.

Always make sure you are approaching your potential supervisor in a professional way. We have provided some guidelines for you on how to contact a supervisor.

Your application will be assessed on a competitive basis.

We take into account your:

• previous academic record
• publication record
• honours and awards
• employment history

A working knowledge of deep learning would be of benefit to someone working on this project.

You will demonstrate academic achievement in the field/s of physics, computer science, electrical/biomedical/software engineering, mathematics, and data science and the potential for scholastic success.

A background or knowledge of image processing and/or computer vision is highly desirable.

Before you apply

Before submitting an application you should:

1. check your eligibility for a Doctor of Philosophy (PhD)
2. prepare your documentation
3. contact Dr Shekhar Chandra (shekhar.chandra@uq.edu.au) to discuss your interest and suitability
4. submit your application by 3 March, 2025 3 March, 2025.

When you apply

You apply for this scholarship when you submit an application for your program. You don’t need to submit a separate scholarship application.

In your application ensure that under the ‘Scholarships and collaborative study’ section you select:

• ‘My higher degree is not collaborative’
• ‘I am applying for, or have been awarded a scholarship or sponsorship'
• ‘Other’, then ‘Research Project Scholarship’ and in the ‘Name of scholarship’ field enter CSIRO-CHANDRA.

Apply now